Anonymised Machine Learning with Distributed -full title is in the event details
Description changed:
This is a joint Scotland Data Science & Technology and Scottish Blockchain Meetup
Title: Towards Anonymization for Learning, Transactions and Credentials Within Distributed Trust Infrastructures
Speakers: Will Abramson, Liam Bell, Bill Buchanan, Adam Hall: Blockpass ID Lab.
Date: Tuesday 25th June 2019 @ 6pm
Outline:
GDPR defines an increased focused on encryption and pseudo-anonymization. But many recent data breaches have shown that organisations often have poor practice when it comes to the anonymisation of personally identifiable information. And so, in future systems, we need to focus on the anonymisation the lowest layers of our data gathering, and then identify methods of revealing the information. But how are we going to apply machine learning into infrastructure which use encrypted data? And how are we going to identify individuals within anonymised infrastructures? And how are we going to be able to regulate for consent, privacy and governance?
This Meetup will outline current research into areas such as machine learning on encrypted data, anonymised and trusted credentials, range proofs, and in the trusted deletion of data.
Speakers:
Anonymised and Distributed Machine Learning, Adam Hall. 20 min - https://www.linkedin.com/in/adam-james-hall-1b0229113
Trusted Deletion of Data, Liam Bell. 20 min - https://www.linkedin.com/in/liamjohnbell
Anonymised and Trusted Credentials, Will Abramson. 20 min.
Range Proofs, Mimblewimble, and other Crypto Magic, Prof Bill Buchanan. 20 min - https://www.linkedin.com/in/billatnapier
Talks start 7pm
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Talk 1 "Commercialising Analytics, ML & AI" - Audrey Leteve (Analytics Consultant) and Leigh Sinton (Analyst) at Merkle Aquila.
Talk 2 "MyData - An Introduction" - Will Abramson, Phd candidate at Blockpass Identity Lab, Edinburgh Napier University.
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Talk 1: "Commercialising Analytics, ML & AI"
As AI & ML extend beyond the confines of the tech office, there is a need to better understand its many applications. This talk aims to debunk some of the myths about AI & ML surrounding expense, accessibility and redundancy and demonstrate how to extract value in commercial AI. Through an exploration of ‘Automation of Inspection Activities’, this talk will detail commercial AI in practice and discuss how to leverage AI fast, accurately and actionably.
Bios: Audrey Leteve is an Analytics Consultant for Merkle Aquila. Audrey has over 7 years of experience working across a various panel of industries such as insurance, utilities, energy, oil and gas, financial services, retail on both client and agency side. She has experience using various statistical and machine learning techniques and is considered a guru in attribution modelling that she applied in various industries.
Leigh Sinton is an Analyst at Merkle Aquila. Leigh is a graduate in both BSc Mathematics and Statistics and also MSc Big Data, with distinction. She has a broad range of skills from employing statistical techniques to clearly communicating technical findings through effective visualisations. She has recently built and developed a deep learning image classification model for a large oil and gas company.
Talk 2 - "MyData - An Introduction"
The talk will cover the MyData principles, the global MyData community and non-profit organization. We will explain how we plan to apply these principles to Scotland through the MyData Scotland hub. How we hope to empower people in Scotland with more control over the data that they create. Most importantly we will talk about how anyone can get involved in the community. To find out more check out https://mydata.org.
Bio: Will Abramson is a PhD candidate at the Blockpass Identity Lab, Edinburgh Napier, researching privacy preserving cryptography. He attended the MyData 2018 conference which opened his eyes to both the current problems around how we manage personal data and the alternative vision that the MyData movement and others are trying to move towards. He sees understanding the personal data space as adjacent to the research he is doing into identity and is excited to be involved in this movement.
Since coming to Edinburgh 6 months ago, he and a couple of others have worked to bring the MyData to Scotland by setting up a local hub. We are very much at the start of that journey but we look forward to sharing our progress and vision for the future.
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Photo by Christine Roy on Unsplash
Scotland Data Science & Technology Meetup and Merkle Aquila are hosting this debate in Merkle Aquila's brand new Edinburgh office.
There will be two teams of two (one arguing either side), each team will cover an opening argument, rebuttal and Q&A.
We are all very used to the idea of bringing together multiple open source tools and solutions to solve client problems. The cost of this approach is usually in low-level technical expertise and time. There are more and more proprietary software solutions that aim to make this experience more accessible, slick, rapid, and integrated. Will these two approaches co-exist in future? Are we moving towards a situation where data science requires financial buy-in to take part at a high level?
Team Free-to-Play
Jasmina Lazić - Chief Data Technologist, Bayes Centre - https://www.linkedin.com/in/jasmina-lazić-850aa9a0
Cathy Mitchell - Assistant Director at Scottish Funding Council - https://www.linkedin.com/in/cathy-mitchell-642a074b
Team Pay-to-Win
Robert Hamlet - Analytical Consultant at Merkle | Aquila - https://www.linkedin.com/in/robert-hamlet
Michael Mulholland - Analytics Consultant at Merkle | Aquila - https://www.linkedin.com/in/michael-mulholland-a781a779
Talking points:
· Are we at or moving towards a situation where data science requires financial buy-in to take part at a high level? Is data science becoming a two-tier system of those skilled enough to build their own technical solutions, and those who must pay for proprietary solutions to compete?
· Are open-source tools sufficient to meet increasing client demands? Are they slick, integrated, rapid, and sufficiently-well supported? Is the gap between the capabilities of open-source and proprietary widening?
· How free is free? Does it represent your best interests? If you didn’t pay for it then perhaps you are the product. Can you rely upon free in an enterprise setting?
· Freedom isn’t free – GDPR saw walled gardens emerge in the digital analytics world. Is it in our best interests long term to pay for software and demand interoperability and competition?
· Are we losing valuable skills by replacing general-purpose low-level hacking skills turn into proficiency in proprietary software suites? Or does paid software allow us to step over the time-consuming groundwork to get at the true technical and/or business challenge?
· We’re used to the idea of bringing together the hard work of many different people to create our solutions for free – will this last?
· Are developers and data scientists sufficiently rewarded by recognition and indirect altruistic benefits to keep releasing their tools/libraries/neural network architectures for free, or will this come to an end?
Note - we've moved this one to the second Tuesday in March to fall within #Datafest 2019.
6.30 for pizza and beers.
Talks start 7pm
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Talk 1 "W3C Data Exchange Working Group - what we are doing, and how you can help" - Dr Peter Winstanley of Scottish Government, and co-Chair of the W3C Data Exchange Working Group
Talk 2 "Activating big data with spatial context to derive deeper insight in socioeconomic research" Dr. Obinna Anejionu, The Urban Big Data Centre.
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Talk 1: "W3C Data Exchange Working Group - what we are doing, and how you can help"
The W3C Data Enchange Working Group is re-designing the vocabulary for publishing data catalogues on the web [DCAT] and creating recommendations on profiles and on content negotiation by application profile. This talk describes the work of the group and the challenges and opportunities that exist for the group and those with an interest in the area of data exchange using internet technology.
Bio: Peter is the co-Chair of the W3C Data Exchange Working Group, a contributor to the "Data on the Web Best Practices" W3C Technical Recommendation, part of the EC Semantic Interoperabliity community, and is skilled at herding cats and wading through treacle.
Talk2 "Activating big data with spatial context to derive deeper insight in socioeconomic research"
The advent of big data analytics has uncovered previously hidden patterns, trends and correlations in various seemingly unrelated variables, leading to new insights. However, much deeper insights, knowledge and wisdom could be obtained from big data sources by activating spatial characteristics inherent in most big data streams and linking these to existing spatial datasets. This is particularly important for efficient management of various socioeconomic issues and challenges and in measuring the impacts of policies on prosperity and quality of life. In this talk, I will explore the strategic importance of spatially-enabled big data social and economic research. I will argue that the potential of big data currently being utilised in various analysis has largely remained unexplored or under-utilised and call for more vibrant deployment of spatial big data analytics in strategic management of the urban areas. I will also talk about what we are doing at the Urban Big Data Centre (UBDC) to achieve this. The UBDC, funded by the Economic and Social Research Council, is a nationwide data service that provides access to urban data, sourced from a variety of public, private and internet sources to academic researchers, local governments and businesses.
Dr. Obinna Anejionu is a Scientific Computing Officer/Spatial Data Scientists at the Urban Big Data Centre, with his primary responsibility focusing on the development of the Spatial Urban Data System (SUDS). He obtained B.Sc in Geoinformatics and Surveying from the University of Nigeria Nsukka, M.Sc GIS and Remote Sensing from the University of Greenwich, London, and PhD in Geography (Remote Sensing and GIS applications in environmental monitoring) from the University of Lancaster.
Prior to his current role, he worked at various universities in the UK including Imperial College London as well as at the University of Nigeria. Obinna’s current research interest focuses on the integration of geospatial technologies (Geomatics, GIS and remote sensing), big data analytics and cloud technology in solving environmental, socio-political and socioeconomic challenges.
His career has progressed into diverse areas with spokes into GIS, Environmental Remote Sensing, Spatial Analytics, Web Mapping, Cloud Technology, Big Data, Data Science, Machine learning. He has published several findings of his research in various high impact international journals.
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Photo by Joshua Sortino on Unsplash
Talks start 7pm
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Talk 1 "Commercialising Analytics, ML & AI" - Marta Portugal, Senior Data Scientist at Merkle Aquila.
Talk 2 Tbc
========================
Talk 1: "Commercialising Analytics, ML & AI"
As AI & ML extend beyond the confines of the tech office, there is a need to better understand its many applications. This talk aims to debunk some of the myths about AI & ML surrounding expense, accessibility and redundancy and demonstrate how to extract value in commercial AI. Through an exploration of ‘Automation of Inspection Activities’, this talk will detail commercial AI in practice and discuss how to leverage AI fast, accurately and actionably.
Bio: Marta Portugal is a Senior Data Scientist at Merkle Aquila. She has experience working in Telecommunications, Insurance and Banking Industry and Oil and Gas Technology. She has most recently been working on image recognition and anomaly detection in the Oil & Gas sector.
Talk 2 - tbc
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Photo by Christine Roy on Unsplash
Data has shape, and that shape has meaning. Even though we typically do not think about data analysis in terms of shape, we do it complicity in our day-to-day practice. Even though being very typical in statistical analysis, linear shapes are not sufficient to describe more complicated and challenging data sets. There are various junctions in the trends, cyclic trends and many more reasons why a simple one to one linear relationship would fail. It is clear that by restricting ourselves to any predefined family of shapes, linear or non linear, we are searching for something in the data that is likely to lead to artificial results. This is implicit to data and does not learn anything from the purpose to model.
Topological Data Analysis (TDA) creates a descriptive model that adapts to the data while making minimal assumptions. In this workshops, by first quantifying and visualising the shape and global features of the underlying data, we aim to demonstrate the power of the TDA integrated into traditional data analysis and machine-learning techniques, achieving augmented superior results in various industrial problem-solving exercises, eg, risk management and banking..
Note - we've moved this one to the second Tuesday in March to fall within #Datafest 2019.
6.30 for pizza and beers.
Talks start 7pm
******************************
Talk 1 "W3C Data Exchange Working Group - what we are doing, and how you can help" - Dr Peter Winstanley of Scottish Government, and co-Chair of the W3C Data Exchange Working Group
Talk 2 The Urban Big Data Centre, Glasgow (details to be finalised)
========================
Talk 1: "W3C Data Exchange Working Group - what we are doing, and how you can help"
The W3C Data Enchange Working Group is re-designing the vocabulary for publishing data catalogues on the web [DCAT] and creating recommendations on profiles and on content negotiation by application profile. This talk describes the work of the group and the challenges and opportunities that exist for the group and those with an interest in the area of data exchange using internet technology.
Bio: Peter is the co-Chair of the W3C Data Exchange Working Group, a contributor to the "Data on the Web Best Practices" W3C Technical Recommendation, part of the EC Semantic Interoperabliity community, and is skilled at herding cats and wading through treacle.
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Photo by Joshua Sortino on Unsplash
Strengths/Weaknesses of different programming Languages/Brain Computer Interf
Description changed:
Presentation 1 - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Presentation 2 - Brain Computer Interface - An Introduction
Description
Brain computer interface (BCI) technology is a growing field of research with many current and potential applications. It may also be referred as BMI (Brain Machine Interface) in some literatures. BCI is applicable in medicine, education, monitoring and control systems, entertainment and many more fields. Typical BCI system consists of sensor devices capturing brain signals. Machine learning algorithms are used to associate the captured signals into cognitive state which can then be translated into computer commands. However, this technology is not flawless. There are challenges such as noise to signal ratio, physical and psychological differences of individuals and ethical matters. This talks will provide an introduction to modern BCI technologies with the following agenda.
What is Brain Computer Interface (BCI)?
How does it works?
Where can it be used?
What are the limitations?
Ethics
Prerequisites for Audience: basic understanding of machine learning concepts such as supervised/unsupervised learning would help but it will be covered briefly.
No prior knowledge of neuroscience is required.
Presenter - Tyn Ong worked as a software developer, system analyst and IT environment manager in Utility and Financial industries for over a decade. He took a career break and recently graduated with MSc in Brain Science from University of Glasgow. He is incubating a startup in BCI while looking for PhD studentship opportunities.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Dr Jasmina Lazić - Chief Data Technologist, Bayes Centre
7.30 – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Tyn Ong
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drinks
Talks start 7pm
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7.00: Uplift Modelling: Spend Less & Sell More.
NickRadcliffe, Stochastic Solutions Limited
//break
7.45 The Anatomy of a Data Science Project
Adam Sroka, Incremental Group
Uplift Modelling: Spend Less & Sell More.
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Uplift modelling is a different approach to customer targeting that directly predicts the *change* in customer behaviour — how much more likely a customer is to stay, or to buy, if treated, compared with if they are not. This talk will explain what uplift modelling is, how it works, and show some real-world results, as well as discussing the applicability of the method and offering some tips on how to get the most out of it.
Targeting with uplift models typically generates more sales or more saved customers, while treating fewer of them thus reducing costs. It also helps to identify customers who should definitely not be treated because of negative effects e.g triggering customer attrition.
BIO: Nick is a practising data scientist with over 30 years experience, from neural networks and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions.
Nick enjoys using his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and has a particular interest in testing and correctness in data science.
Nick is also a Visiting Professor of Mathematics at Edinburgh University.
The Anatomy of a Data Science Project
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Title:
Anatomy of a Data Science Project
This session will walk through what typically goes into a good data science solution and some advice on how to structure a project for ease of understanding and repeatability.
Bio: (https://incrementalgroup.co.uk/about/people/adam-sroka-senior-data-scientist/)
Adam is Incremental’s Senior Data Scientist. He is responsible for developing data and AI solutions for organisations and helping them make sense of large quantities of data so they can drive results.
Adam specialises in predictive modelling and taking large, complex data flows and turning them into robust, manageable pipelines. Adam is passionate about helping organisations realise the importance of good foundational data practices to set them up for AI/ML optimisation in the future. Adam regularly speaks at technology meet up and events on and around this topic.
Adam first realised the power of machine learning during his Doctorate of Engineering at the University of Strathclyde. Since then he has worked as a data scientist in a number of industries including online retail developing predictive models for some of the UK’s most recognisable online and high street retailers. Adam also spent time in insurance delivering complex pricing models and real-time optimisations.
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Photo by Kari Shea on Unsplash
The adoption of analytics has accelerated over the last decade, and most organisations have created or developed an analytics function to drive insight from data. However, organisations often face challenges in being able to deliver true business value through their analytics team, and it can be difficult to obtain the right blend of skills to make sure the team is set up for success. In this talk, I’ll share my experience of working in analytics functions in both consulting and in industry and will share thoughts on what creates an effective analytics team, considering the important skills and capabilities that can drive success and add true value to an organisation.
Elizabeth is the Head of Analytics and BI for Aggreko, and leads a team of data scientists who use data to drive value across the business. She has spent the last 12 years working in a variety of industries, helping them use their data to solve business problems. She has a passion for helping people understand the value of data, and loves to communicate complex ideas in a simple way to enable effective insight-driven decision making.
Presentation 2 - Uplift Modelling: Spend Less & Sell More - Nick Radcliffe, Stochastic Solutions Limited
https://www.linkedin.com/in/njradcliffe
Uplift modelling is a different approach to customer targeting that directly predicts the *change* in customer behaviour—how much more likely a customer is to stay, or to buy, if treated, compared with if they are not. This talk will explain what uplift modelling is, how it works, and show some real-world results, as well as discussing the applicability of the method and offering some tips on how to get the most out of it.
Targeting with uplift models typically generates more sales or more saved customers, while treating fewer of them thus reducing costs. It also helps to identify customers who should definitely not be treated because of negative effects e.g triggering customer attrition.
Nick is a practising data scientist with over 30 years experience, from neural networks and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions.
Nick enjoys using his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and has a particular interest in testing and correctness in data science.
Nick is also a Visiting Professor of Mathematics at Edinburgh University.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Elizabeth Hollinger - Head of Analytics & BI at Aggreko
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Nick Radcliffe, Stochastic Solutions Limited
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Talks start 7pm
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Talk1>> Uplift Modelling: Spend Less & Sell More Nick Radcliffe, Stochastic Solutions Limited
DESCRIPTION:
Uplift modelling is a different approach to customer targeting that directly predicts the *change* in customer behaviour — how much more likely a customer is to stay, or to buy, if treated, compared with if they are not. This talk will explain what uplift modelling is, how it works, and show some real-world results, as well as discussing the applicability of the method and offering some tips on how to get the most out of it.
Targeting with uplift models typically generates more sales or more saved customers, while treating fewer of them thus reducing costs. It also helps to identify customers who should definitely not be treated because of negative effects e.g triggering customer attrition.
BIO: Nick is a practising data scientist with over 30 years experience, from neural networks and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions.
Nick enjoys using his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and has a particular interest in testing and correctness in data science.
Nick is also a Visiting Professor of Mathematics at Edinburgh University.
Talk 2 tbc
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Photo by Kari Shea on Unsplash
Strengths / weaknesses of different programming Languages /Brain Computer Interf
Description changed:
Presentation 1 - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Presentation 2 - Brain Computer Interface - An Introduction
Description
Brain computer interface (BCI) technology is a growing field of research with many current and potential applications. It may also be referred as BMI (Brain Machine Interface) in some literatures. BCI is applicable in medicine, education, monitoring and control systems, entertainment and many more fields. Typical BCI system consists of sensor devices capturing brain signals. Machine learning algorithms are used to associate the captured signals into cognitive state which can then be translated into computer commands. However, this technology is not flawless. There are challenges such as noise to signal ratio, physical and psychological differences of individuals and ethical matters. This talks will provide an introduction to modern BCI technologies with the following agenda.
What is Brain Computer Interface (BCI)?
How does it works?
Where can it be used?
What are the limitations?
Ethics
Prerequisites for Audience: basic understanding of machine learning concepts such as supervised/unsupervised learning would help but it will be covered briefly. No prior knowledge of neuroscience is required.
Presenter - Tyn Ong worked as a software developer, system analyst and IT environment manager in Utility and Financial industries for over a decade. He took a career break and recently graduated with MSc in Brain Science from University of Glasgow. He is incubating a startup in BCI while looking for PhD studentship opportunities.
https://www.linkedin.com/in/tynong/
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Dr Jasmina Lazić - Chief Data Technologist, Bayes Centre - https://www.linkedin.com/in/jasmina-lazić-850aa9a07.30 PM 7.30 – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Tyn Ong - https://www.linkedin.com/in/tynong/
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Strengths and weaknesses of different programming languages
Description changed:
Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Dr Jasmina Lazić - Chief Data Technologist, Bayes Centre - https://www.linkedin.com/in/jasmina-lazić-850aa9a07.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: TBC
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Talks start 7pm
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Talk 1 "#ScotWiki and other stories" - Dr Sara Thomas
Sarah, who is Scotland Programme Coordinator at Wikimedia UK, has been in post since April 2018. She was the Wikimedian in Residence at the Scottish Library and Information Council (2017-2018), and at Museums Galleries Scotland (2015 - 2016).
Sara joins us to talk about the work that Wikimedia UK is doing across Scotland, in libraries, education and heritage.
Talk 2 "Automated Artificial Intelligence" Dr Andy Starkey
The explosion of activity and interest in AI and machine learning has reached all industry sectors which has meant that the data scientists required to build these solutions are in high demand. Research at the University of Aberdeen has focussed on the development of automated methods of analysing data, and this talk will give an overview of the normal process of building AI solutions and then the improvements to be made by automating this process. The talk will give examples of where it has been applied and show the type of results that can be obtained and also some currently work being undertaken with industry.
Dr Andrew Starkey is a lecturer in the School of Engineering at the University of Aberdeen. He has over 20 years of experience in Artificial Intelligence and currently is supervisor of a number of PhD students who are all involved in work related to automated data analysis using AI techniques or autonomous learning. He has previously been involved in research work with AI that resulted in commercial licenses that won a number of industry awards. He is CEO of a spinout company from the University that specialises in automated data analysis using AI technology. He has recently won research funding for projects with Halliburton and WFS in the area of the application of AI technologies.
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
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Photo by James L.W on Unsplash
Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Ted Dunning - Chief Application Architect at MapR - https://www.linkedin.com/in/teddunning
Kubernetes and Big Data
The folk wisdom has always been that when running stateful applications inside containers, the only viable choice is to externalize the state so that the containers themselves are stateless or nearly so. Keeping large amounts of state inside containers is possible, but it’s considered a problem because stateful containers generally can’t preserve that state across restarts.
In practice, this complicates the management of large-scale Kubernetes-based infrastructure because these high-performance storage systems require separate management. In terms of overall system management, it would be ideal if we could run a software-defined storage system directly in containers managed by Kubernetes, but that has been hampered by lack of direct device access and difficult questions about what happens to the state on container restarts.
Ted Dunning describes recent developments that make it possible for Kubernetes to manage both compute and storage tiers in the same cluster. Container restarts can be handled gracefully without loss of data or a requirement to rebuild storage structures and access to storage from compute containers is extremely fast. In some environments, it’s even possible to implement elastic storage frameworks that can fold data onto just a few containers during quiescent periods or explode it in just a few seconds across a large number of machines when higher speed access is required.
The benefits of systems like this extend beyond management simplicity, because applications can be more Agile precisely because the storage layer is more stable and can be uniformly accessed from any container host. Even better, it makes it a snap to configure and deploy a full-scale compute and storage infrastructure
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Ted Dunning - Chief Application Architect at MapR
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Anatomy of a Data Science Project – this session will walk through what typically goes into a good data science solution and some advice on how to structure a project for ease of understanding and repeatability.
An introduction to network analysis – What is Network analysis, where it comes from with some examples and what it can be used for.
Speakers:
Adam Sroka - Senior Data Scientist at Incremental Group - https://www.linkedin.com/in/aesroka
Ricardo Antunes - Data Scientist at Incremental Group - https://www.linkedin.com/in/ricardo-antunes-764755123
Adam and Ricardo are the two leading Data Scientists at Incremental Group helping a wide range of Organisations with Data Science projects. Adam first starting using machine learning during his Doctorate of Engineering at the University of Strathclyde. He has worked as a data scientist since then, working primarily with large data volumes and taking models from experimentation through to production. Ricardo original trained as a marine biologist where he learned data science as part of his Doctoral research project on whales. He has working in a wide range of academic and consultancy roes.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 08.00 PM Presentations / Q & A Session
8.00 PM - 9.00 PM: Networking and Drink
How do we create a culture of sustainable business growth through Data?
Description changed:
Sign up here - https://www.eventbrite.co.uk/e/the-scotsman-conferences-data-innovation-series-tickets-51802479611
This expert discussion is part of the Scotsman’s Data Driven Innovation series.
The panel will explore how important is it for companies to develop a culture which promotes growth through data and encourages the development of new and existing talent within their organisations. The debate will place data skills in a wider context and consider how important they are in enabling companies in Scotland to embrace the data opportunity:
Why is data key to Scotland’s future economic growth and how do we ensure broad adoption and data innovation across all sectors?
What needs to be done to address the digital skills gap to develop a diverse and globally competitive talent pool, and research infrastructure that contributes more to the Scottish economy?
What are the key data challenges that are facing businesses on the ground and how can these be overcome?
Agenda:
11:30am: Arrivals and refreshments
12:00pm: Panel discussion and Q&A sessions
1:30pm: Networking
2:00pm: Close
The panel includes:
Paul Forrest – Chairman at MBN Solutions - https://www.linkedin.com/in/pdf66
Elizabeth Hollinger – Head of Analytics and BI for Aggreko - https://www.linkedin.com/in/elizabeth-hollinger-31055234
David Smith – Sector Director Digital Technology at Scottish Enterprise - https://www.linkedin.com/in/david-smith-1b0155
Ed Broussard – Co-founder & CEO at Mudano - https://www.linkedin.com/in/broussarded
David Tracy – Chief Analytics Officer at Castlight Financial - https://www.linkedin.com/in/david-tracy-003415124
Dr Katharina Kaesehage - University of Edinburgh -https://www.linkedin.com/in/kathi-kaesehage-114a6018
Supporters
MBN solutions - www.mbnsolutions.com
Scottish Enterprise
Edinburgh University
Venue
The University of Edinburgh
Holyrood Campus, Paterson's Land Building
Edinburgh, EH8 8AQ
Scotland’s Data Science & Technology Meetup at DIGIT Expo On 14th November.
This hour long event will be one of many on an excellent day - Register now for DIGIT Expo
The event is free to attend - Register online now at: https://www.digitexpo.uk
Scotland’s Data Science & Technology Meetup will be hosting a guest session at DIGIT’s inaugural Tech Expo at the EICC in Edinburgh.
The session will explore how to improve the process of delivering organisational value from data science.
The session will be run as a panel discussion, hosted by Paul Forrest (https://www.linkedin.com/in/pdf66 ) Chairman of MBN Solutions, joined by an impressive line-up of data practitioners from Scotland’s business community.
Panellists include:
• Gillian Docherty, CEO, The Data Lab - https://www.linkedin.com/in/gillian-docherty
• Martin Thorn, Senior Manager: Decisioning, Analytics & AI, CYBG - https://www.linkedin.com/in/martin-thorn
• Dave Oliver, Head of PBB MI, RBS - https://www.linkedin.com/in/dave-oliver-a8083417
• Sorcha Lorimer, Founder and Data Privacy Specialist, Sympatico - https://www.linkedin.com/in/sorchalorimer
DIGIT Expo is Scotland largest enterprise IT & Digital showcase, with over 1000 delegates, 30 speakers, 60 exhibitors and 4 conference streams.
Keynote Speakers:
• Karl Surmacz, Principal Data Scientist, McLaren
• Craig Fenton, Director of Strategy & Operations, Google
• Jessie Link, Head of Engineering, Twitter
• Jacqueline Guichelaar, CIO, Thomson Reuters
• Ian Trump, Head of Cyber Security, AmTrust International
• Candace Kuss, Director of Social Media, H+K Strategies
Talks start 7pm
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Talk 1 SmartRural - The journey and anatomy of a data point.
You’ve heard about “Farm to Fork”, but what about “Farm to Server and back Again”? How do we gather new actionable data and add value to the rural ecosystem?
SmartRural is establishing a user owned cooperative LPWAN to be deployed across rural Scotland. The aim of this is to bring digital connectivity and innovation to every corner of Scotland, uniquely servicing the Scottish Government’s Digital Strategy objective of “Outside In”. This new infrastructure will facilitate an explosion in LPWAN IoT with a accompanying tsunami of data, but what does this new data actually look like, how will it arrive, how can we access it and what can we do with it?
Talk 2 - TrustLens Project
The Internet of Things (IoT) concept refers to the seamless integration of physical objects, sensors and mobile devices onto the Internet. The IoT encompasses many different technologies, services and standards, however IoT solutions comprise more than just the hardware and software necessary to realize the technical infrastructure. They also include the human actors, organisations, policies and regulatory systems involved. With some estimates predicting 50 billion devices by 2020, and the proportion of data collected passively through machine-to-machine transactions surpassing that actively generated by individuals - solutions are needed to strengthen trust. We work with communities and individuals to explore what it means to realise solutions that are transparent, accountable, and which empower end-users. The TrustLens is our vision of a future toolset that will enable individuals, and the communities of which they are a part, to better understand and manage the data about them.
Dr Naomi Jacobs is a Research Fellow at the University of Aberdeen whose various work focuses on the societal impacts of technology in digital and physical spaces. Naomi's research interests include interdisciplinarity, digital public space, and the impact on communities of internet of things technologies, particularly with regards trust and transparency.
Dr Milan Markovic is a Research Fellow at the University of Aberdeen with interests in semantic modelling of trust and transparency in the IoT domain. His current work is centred around the design and utilisation of semantic models for capturing provenance of IoT deployments and automated privacy risk assessment mechanisms.
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
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Photo by Andreas Dress on Unsplash
Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Presentation 2 - Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Presentation 2 - Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Talks start 7pm
******************************
Talk 1 "#ScotWiki and other stories" - Dr Sara Thomas
Sarah, who is Scotland Programme Coordinator at Wikimedia UK, has been in post since April 2018. She was the Wikimedian in Residence at the Scottish Library and Information Council (2017-2018), and at Museums Galleries Scotland (2015 - 2016).
Sara joins us to talk about the work that Wikimedia UK is doing across Scotland, in libraries, education and heritage.
Talk 2 (tbc)
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
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Photo by James L.W on Unsplash
Talks start 7pm
******************************
Talk 1 SmartRural - The journey and anatomy of a data point.
You’ve heard about “Farm to Fork”, but what about “Farm to Server and back Again”? How do we gather new actionable data and add value to the rural ecosystem?
SmartRural is establishing a user owned cooperative LPWAN to be deployed across rural Scotland. The aim of this is to bring digital connectivity and innovation to every corner of Scotland, uniquely servicing the Scottish Government’s Digital Strategy objective of “Outside In”. This new infrastructure will facilitate an explosion in LPWAN IoT with a accompanying tsunami of data, but what does this new data actually look like, how will it arrive, how can we access it and what can we do with it?
Talk 2 - TrustLens Project
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by Andreas Dress on Unsplash
Talks start 7pm
******************************
Talk 1 SmartRural - The journey and anatomy of a data point.
You’ve heard about “Farm to Fork”, but what about “Farm to Server and back Again”? How do we gather new actionable data and add value to the rural ecosystem?
SmartRural is establishing a user owned cooperative LPWAN to be deployed across rural Scotland. The aim of this is to bring digital connectivity and innovation to every corner of Scotland, uniquely servicing the Scottish Government’s Digital Strategy objective of “Outside In”. This new infrastructure will facilitate an explosion in LPWAN IoT with a accompanying tsunami of data, but what does this new data actually look like, how will it arrive, how can we access it and what can we do with it?
Talk 2 (tbc - WikiMedia / Wiki Data)
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by Andreas Dress on Unsplash
Talks start 7pm
******************************
Talk 1 Alan Russell - “Visualising the ownership of Scottish football”
Alan Russell will share insights from his work on using data visualisations using Tableau to explore Scottish football clubs’ approach to supporter engagement and transparency, and to improve visibility of clubs’ ownership through the ‘SDS Index’. Alan will also share some earlier work done to improve supporters’ understanding of the history and ownership structure of the club he supports, Raith Rovers FC.
Bio:
Alan Russell is CEO of Supporters Direct Scotland and Chair of the Raith Supporters Trust, two organisations that help supporters gain influence in the running and ownership of their club. In his spare moments away from football he works as a management consultant, supporting global and local clients in the corporate and non-corporate sectors to develop and implement strategy.
Talk 2 -Dr. Graham McGlashan
“The Value in Data and How to Protect It – Intellectual Property (IP) for Data Related Businesses”
Where is the value in a data related business? Is it in the data itself? Perhaps it is in the way the data is collected, analysed or used? Often these intangible assets are the result of a significant amount of skill, expertise, insight, experience, time and money. For many companies, these intangible assets can contribute a sizable amount to the value of a business.
Intellectual property (IP) protection is intended to cover these very assets. However, modern IP has its roots in systems that date back hundreds of years and often struggles to adapt to modern technologies such as data based industry and machine learning. This talk is intended to give an introduction to how intellectual property protection applies to data related ideas and businesses, and give some suggestions of ways in which it can be used.
Biog
Dr Graham McGlashan is a Partner at Marks & Clerk, the largest firm of specialist Patent & Trademark Attorneys in the UK. Graham specialises in computer implemented inventions, data related concepts, machine learning, virtual/augmented reality, electronics, networks, communications and sensors. He advises a range of clients from some of the largest and most famous multinational tech companies, to small Scottish start-ups looking to make a difference. Before entering the IP profession, Graham worked in R&D for both multi-nationals and small spin-outs and was a named inventor on a number of patents before changing track to help others with their IP strategy and protection.
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by Click and Boo on Unsplash
Talks start 7pm
******************************
Talk 1 Alan Russell - “Visualising the ownership of Scottish football”
Alan Russell will share insights from his work on using data visualisations using Tableau to explore Scottish football clubs’ approach to supporter engagement and transparency, and to improve visibility of clubs’ ownership through the ‘SDS Index’. Alan will also share some earlier work done to improve supporters’ understanding of the history and ownership structure of the club he supports, Raith Rovers FC.
Bio:
Alan Russell is CEO of Supporters Direct Scotland and Chair of the Raith Supporters Trust, two organisations that help supporters gain influence in the running and ownership of their club. In his spare moments away from football he works as a management consultant, supporting global and local clients in the corporate and non-corporate sectors to develop and implement strategy.
Talk 2 -Dr. Graham McGlashan
“The Value in Data and How to Protect It – Intellectual Property (IP) for Data Related Businesses”
Where is the value in a data related business? Is it in the data itself? Perhaps it is in the way the data is collected, analysed or used? Often these intangible assets are the result of a significant amount of skill, expertise, insight, experience, time and money. For many companies, these intangible assets can contribute a sizable amount to the value of a business.
Intellectual property (IP) protection is intended to cover these very assets. However, modern IP has its roots in systems that date back hundreds of years and often struggles to adapt to modern technologies such as data based industry and machine learning. This talk is intended to give an introduction to how intellectual property protection applies to data related ideas and businesses, and give some suggestions of ways in which it can be used.
Biog
Dr Graham McGlashan is a Partner at Marks & Clerk, the largest firm of specialist Patent & Trademark Attorneys in the UK. Graham specialises in computer implemented inventions, data related concepts, machine learning, virtual/augmented reality, electronics, networks, communications and sensors. He advises a range of clients from some of the largest and most famous multinational tech companies, to small Scottish start-ups looking to make a difference. Before entering the IP profession, Graham worked in R&D for both multi-nationals and small spin-outs and was a named inventor on a number of patents before changing track to help others with their IP strategy and protection.
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by Filios Sazeides on Unsplash.
7pm “The need for Awesome Data Quality” - Jan Saevanee
Abstract
Do you hate inconsistent excel worksheets? Have you heard the saying rubbish in rubbish out? We want to share our story on these issues and search for a solution with you.
Due to unclear requirements, unformatted and inconsistent data structure the Business Intelligence team had a setback while creating data visualization reports. The team spent a lot of time in the ETL process. Which meant that we created less valuable reports. The value was lost because we did not understand the vision and the story behind the need for such visualizations. Our proposal is to create a data pipeline and qualification process.”
Jan is part of Business Intelligence team at Aberdeen City Council. The BI team is responsible for creating data visualisation to help decision makers make a better decisions based on evidence. Jan will present the topic alongside Real and Maksim, internship students from university of Aberdeen.
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Talk 2 - Dr. Caroline Chibelushi
AI and the innovate UK Knowledge Transfer Network (KTN)
Caroline will speak about:
- KTN and its support to business
- Robotics and Artificial Intelligence (RAI) Industry Showcase 2019 (see https://dev.ktn-uk.co.uk/preview?type=news&id=21879)
- RAI Pichfest
- To ask the audience if they could come forward to be recorded for a case study.
- Sectors which from our experience have high demand for AI.
===============================
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by rawpixel on Unsplash
Talks start 7pm
******************************
Talk 1 Alan Russell - “Visualising the ownership of Scottish football”
Alan Russell will share insights from his work on using data visualisations using Tableau to explore Scottish football clubs’ approach to supporter engagement and transparency, and to improve visibility of clubs’ ownership through the ‘SDS Index’. Alan will also share some earlier work done to improve supporters’ understanding of the history and ownership structure of the club he supports, Raith Rovers FC.
Bio:
Alan Russell is CEO of Supporters Direct Scotland and Chair of the Raith Supporters Trust, two organisations that help supporters gain influence in the running and ownership of their club. In his spare moments away from football he works as a management consultant, supporting global and local clients in the corporate and non-corporate sectors to develop and implement strategy.
Talk 2 - Details to follow.
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by Filios Sazeides on Unsplash.
7pm “The need for Awesome Data Quality” - Jan Saevanee
Abstract
Do you hate inconsistent excel worksheets? Have you heard the saying rubbish in rubbish out? We want to share our story on these issues and search for a solution with you.
Due to unclear requirements, unformatted and inconsistent data structure the Business Intelligence team had a setback while creating data visualization reports. The team spent a lot of time in the ETL process. Which meant that we created less valuable reports. The value was lost because we did not understand the vision and the story behind the need for such visualizations. Our proposal is to create a data pipeline and qualification process.”
Jan is part of Business Intelligence team at Aberdeen City Council. The BI team is responsible for creating data visualisation to help decision makers make a better decisions based on evidence. Jan will present the topic alongside Real and Maksim, internship students from university of Aberdeen.
******************************
7.45 pm Talk 2 - Details to follow.
===============================
Thanks to MBN Solutions, Data Lab Scotland, and Scotland IS for sponsoring this event.
*****************************
Photo by rawpixel on Unsplash
Ashrith Barthur - Security Scientist at H2O - https://www.linkedin.com/in/abarthur
In this talk, Ashrith will be introducing you to the idea of using machine learning for detecting money laundering. The idea behind using ML for detecting money laundering is that the current rules-based engine have limited visibility into money movement. And as models learn the nuances of money movement, especially illegal, much better money laundering detection is possible.
Ashrith Barthur is a Security Scientist at H2O currently working on algorithms that detect anomalous behaviour in user activities, network traffic, attacks, financial fraud and global money movement. He has a PhD from Purdue University in the field of information security, specialized in Anomalous behaviour in DNS protocol.
Presentation 2 -An Introduction to H2O Driverless AI - Automatic Machine Learning for the Enterprise
Jo-fai (Joe) is a data science evangelist at H2O.ai. - https://www.linkedin.com/in/jofaichow
Before joining H2O, he was in the business intelligence team at Virgin Media where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab as a data science evangelist promoting products via blogging and giving talks at external events. Joe has a background in water engineering. Before his data science journey, he was an EngD researcher at STREAM Industrial Doctorate Centre working on machine learning techniques for drainage design optimization. Prior to that, he was an asset management consultant specialized in data mining and constrained optimization for the utilities sector in UK and abroad. He also holds a MSc in Environmental Management and a BEng in Civil Engineering.
H2O will be giving away special prizes at the end of the event.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Ashrith Barthur - Security Scientist at H2O - https://www.linkedin.com/in/abarthu
7:30 PM – 7:45 PM: Q & A Session
7:45 PM – 8:15 PM: Jo-fai (Joe) is a data science evangelist at H2O.ai. - https://www.linkedin.com/in/jofaichow
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
September's data meet-up is a showcase of projects of students who have just completed their MSc Data Science and AI at Aberdeen University and Robert Gordon University.
We've five short presentations, each of around 20 mins plus questions and loads of networking!
**************************
18:30 pizza and beer.
**************************
7pm - Talk 1. Susan Krueger - MSc Data Science, RGU:
"Visual Document Mining - making sense of seemingly unrelated collections of textual data."
***************************
7.25 pm - Talk 2. Wenjun Liao (Claude) - MSc Artificial Intelligence (AU)
"Using ensemble-based systems to tackle fake news."
**************************
7.50 pm - Talk 3. Ian Watt - MSc Data Science, RGU:
"Blocklists, Bubbles and Cliques: identifying and measuring the effects of Twitter echo-chambers in the Scottish independence debate."
***************************
8.15 pm - Talk 4. Chidozie Victor Nnachor, Aberdeen Uni
Database for Organic Rotation at Scotland's Rural College
****************************
8.40 - Talk 5. Miruna Clinciu, AU
Optimisation of oil and gas reservoirs by prediction of time-series data, using the SAX Algorithm and Long Short Term Memory(LSTM) neural networks.
Abstracts:
Susan Kreuger:
What is visual document mining and how it can be used to make sense of vast and seemingly unrelated collections of text data. We'll look at a simple visual document mining tool in action and go under the hood to learn how it mines text, using unsupervised machine learning to uncover hidden patterns and associations within the collection, which are then visualised for analyses and discovery by the user. We will explain two of the many approaches to machine learning for text data: topic modelling and the k-means clustering algorithm.
----------------------------
Wenjun Liao (Claude):
Tackling fake news: how ensemble-based systems can outperform the state-of- the-art algorithms in news stance detection task with relatively simple architecture and easy implementation.
---------------------------
Ian Watt:
Using novel method to detect who actually uses a prominent distributed Twitter blocklist, and creating network graphs of 116 million users, we analyse whether or not using a blocklist exacerbates the echo-chamber effects which are prominent in social media.
----------------------------
Chidozie Victor Nnachor:
The project is a centralised database system for Scotland's Rural college Cereal Yield field trials. The web application provides consistency and availability to the research data generated by the Aberdeen arm of the college. Other features include owner-initiated data uploads, User access hierarchy and fluid and automated audit trail of the Database. It also presents visualisation data for public consumption. It was developed by a team of 6 Msc Students at the University of Aberdeen.
----------------------------
Miruna Clinciu:
The oil and gas industry depends on physics based models to predict future performance of oil and gas reservoirs, with a large amount of data generated from well sensors.
With a greater uncertainty on historical data there is a need of exploring how we could use other data attributes collected at various points in our systems to close the gap, narrow uncertainties, and improve performance.
The water cut data is considered the key for optimization of the oil and gas reservoir and the forecasting of the point when the production should be shut down leads to increased profits.
The aim of this project is to predict the water cut, represented as time-series data, using the SAX Algorithm and Long Short Term Memory(LSTM) neural networks. For achieving an accurate forecasting model we need to fill the gaps by predicting the inferred data using different machine learning techniques.
*****************************
Thanks to MBN Solutions, Data Lab Scotland and Scotland IS for sponsoring this event.
Photo by Hal Gatewood on Unsplash
September's data meet-up is a showcase of projects of students who have just completed their MSc Data Science and AI at Aberdeen University and Robert Gordon University.
We've four short presentations, each of around 20 mins plus questions and loads of networking!
**************************
18:30 pizza and beer.
**************************
7pm - Talk 1. Susan Krueger - MSc Data Science, RGU:
"Visual Document Mining - making sense of seemingly unrelated collections of textual data."
**************************
8pm - Talk 3. Ian Watt - MSc Data Science, RGU:
"Blocklists, Bubbles and Cliques: identifying and measuring the effects of Twitter echo-chambers in the Scottish independence debate."
***************************
8.30 pm - Talk 4 (tbc) Aberdeen Uni
****************************
Abstracts:
Susan Kreuger:
In this talk, you'll find out what visual document mining is and how it can be used to make sense of vast and seemingly unrelated collections of text data. We'll look at a simple visual document mining tool in action and go under the hood to learn how it mines text and uses unsupervised machine learning to uncover hidden patterns and associations within the collection, which are then visualised for analyses and discovery by the user. My aim will be to unpack and explain two of the many approaches to machine learning for text data: topic modelling and the k-means clustering algorithm. If there's time, we may look at the Python code and tooling used in development as well as tips for storytelling with data.
----------------------------
Wenjun Liao (Claude):
Tackling fake news: how ensemble-based systems can outperform the state-of- the-art algorithms in news stance detection task with relatively simple architecture and easy implementation.
---------------------------
Ian Watt:
Using novel method to detect who actually uses a prominent distributed Twitter blocklist, and creating network graphs of 116 million users, we analyse whether or not using a blocklist exacerbates the echo-chamber effects which are prominent in social media.
*****************************
Thanks to MBN Solutions, Data Lab Scotland and Scotland IS for sponsoring this event.
Photo by Hal Gatewood on Unsplash
Ashrith Barthur - Security Scientist at H2O - https://www.linkedin.com/in/abarthur
In this talk, Ashrith will be introducing you to the idea of using machine learning for detecting money laundering. The idea behind using ML for detecting money laundering is that the current rules-based engine have limited visibility into money movement. And as models learn the nuances of money movement, especially illegal, much better money laundering detection is possible.
Ashrith Barthur is a Security Scientist at H2O currently working on algorithms that detect anomalous behaviour in user activities, network traffic, attacks, financial fraud and global money movement. He has a PhD from Purdue University in the field of information security, specialized in Anomalous behaviour in DNS protocol.
Presentation 2 -An Introduction to H2O Driverless AI - Automatic Machine Learning for the Enterprise
Jo-fai (Joe) is a data science evangelist at H2O.ai. - https://www.linkedin.com/in/jofaichow
Before joining H2O, he was in the business intelligence team at Virgin Media where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab as a data science evangelist promoting products via blogging and giving talks at external events. Joe has a background in water engineering. Before his data science journey, he was an EngD researcher at STREAM Industrial Doctorate Centre working on machine learning techniques for drainage design optimization. Prior to that, he was an asset management consultant specialized in data mining and constrained optimization for the utilities sector in UK and abroad. He also holds a MSc in Environmental Management and a BEng in Civil Engineering.
H2O will be giving away special prizes at the end of the event.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Ashrith Barthur - Security Scientist at H2O - https://www.linkedin.com/in/abarthu
7:30 PM – 7:45 PM: Q & A Session
7:45 PM – 8:15 PM: Jo-fai (Joe) is a data science evangelist at H2O.ai. - https://www.linkedin.com/in/jofaichow
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
David is responsible for ensuring Castlight’s products leverage the latest state-of-the-art data science techniques, and for creating innovative new products to help lending institutions and consumers take advantage of the new opportunities afforded by open banking, by giving them the tools they need to make better financial decisions.
David has built and led data science teams in the UK and internationally, most recently founding and developing the data science team at web-based fantasy sports company FanDuel, where he mechanised advanced methods of data modelling to predict the behaviour of its 6 million registered users. David has also worked widely across the UK and Europe’s insurance sector at Kwik-Fit Insurance, Ageas and Tesco Bank. During his time in the analytics department at Tesco Bank he was responsible for using data science to support the marketing function by building tools to forecast consumer behaviour and develop evidence-based “what-if” scenario modelling.
Presentation 2 - Richard Carter - Data Scientist - Previse
Previse (http://previ.se) is one of The FinTech50 in 2018, and was recently named Digital Service Company of the Year in the Digital Technology Leaders Awards. Previse's innovative technology uses machine learning to enable corporate buyers to pay their suppliers instantly upon receipt of an invoice. Suppliers benefit from this by eliminating the need for expensive short-term credit and gaining certainty around cash-flows. Buyers benefit by building a reputation as a business that treats suppliers fairly, thus becoming a "buyer of choice".
Richard Carter is a Data Scientist at Previse. In his previous role at The Data Lab Richard spoke to and advised hundreds of data businesses in Scotland. He feels that Previse has the most compelling data-led business case he has seen, and hence joined the company three months ago.
Richard's background is one of mathematical modelling and finance. At the start of his career he worked in the City, including on the commodities trading desk at Goldman Sachs. He returned to academia to complete a PhD on machine learning applied to poker, then built algorithmic trading models to bet on sports for eight years as a professional gambler.
His work at The Data Lab and as an independent consultant has given Richard exposure to a broad range of data science challenges, including quality assessment in the whisky industry, predicting delayed discharges in the Scottish NHS, and the construction of an automated Bitcoin trader.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: David Tracy - Chief Analytics Officer - Castlight Financial
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Richard Carter - Data Scientist - Previse
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
David is responsible for ensuring Castlight’s products leverage the latest state-of-the-art data science techniques, and for creating innovative new products to help lending institutions and consumers take advantage of the new opportunities afforded by open banking, by giving them the tools they need to make better financial decisions.
David has built and led data science teams in the UK and internationally, most recently founding and developing the data science team at web-based fantasy sports company FanDuel, where he mechanised advanced methods of data modelling to predict the behaviour of its 6 million registered users. David has also worked widely across the UK and Europe’s insurance sector at Kwik-Fit Insurance, Ageas and Tesco Bank. During his time in the analytics department at Tesco Bank he was responsible for using data science to support the marketing function by building tools to forecast consumer behaviour and develop evidence-based “what-if” scenario modelling.
Presentation 2 - Richard Carter - Data Scientist - Previse
Previse (http://previ.se) is one of The FinTech50 in 2018, and was recently named Digital Service Company of the Year in the Digital Technology Leaders Awards. Previse's innovative technology uses machine learning to enable corporate buyers to pay their suppliers instantly upon receipt of an invoice. Suppliers benefit from this by eliminating the need for expensive short-term credit and gaining certainty around cash-flows. Buyers benefit by building a reputation as a business that treats suppliers fairly, thus becoming a "buyer of choice".
Richard Carter is a Data Scientist at Previse. In his previous role at The Data Lab Richard spoke to and advised hundreds of data businesses in Scotland. He feels that Previse has the most compelling data-led business case he has seen, and hence joined the company three months ago.
Richard's background is one of mathematical modelling and finance. At the start of his career he worked in the City, including on the commodities trading desk at Goldman Sachs. He returned to academia to complete a PhD on machine learning applied to poker, then built algorithmic trading models to bet on sports for eight years as a professional gambler.
His work at The Data Lab and as an independent consultant has given Richard exposure to a broad range of data science challenges, including quality assessment in the whisky industry, predicting delayed discharges in the Scottish NHS, and the construction of an automated Bitcoin trader.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: David Tracy - Chief Analytics Officer - Castlight Financial
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Richard Carter - Data Scientist - Previse
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Castlight Financial, the Glasgow-based financial capability company recruited internationally experienced data science and analytics innovator, David Tracy, as Chief Analytics Officer.
David has built and led data science teams in the UK and internationally, most recently founding and developing the data science team at web-based fantasy sports company FanDuel, where he mechanised advanced methods of data modelling to predict the behaviour of its 6 million registered users. David has also worked widely across the UK and Europe’s insurance sector at Kwik-Fit Insurance, Ageas and Tesco Bank. During his time in the analytics department at Tesco Bank he was responsible for using data science to support the marketing function by building tools to forecast consumer behaviour and develop evidence-based “what-if” scenario modelling.
Presentation 2 - TBC
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: David Tracy - Chief Analytics Officer - Castlight Financial
7:30 PM – 7:45 PM: Q & A Session
7:45 PM – 8:15 PM: TBC
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Expired changed:Not ExpiredEdited at by jamesjmbtechnology