Join us for a night of Python talks at the central Skyscanner office in Glasgow. We will have two talks. Skyscanner will be providing us with food and drinks.
Doors open at 17:30, please arrive by 18:30 at the latest.
Pizza will arrive at 18:00.
First talks will start at 18:30.
Talk 1: Flow-Based Programming with Luigi for doing Science
By: Harry Ambrose Jack
The Flow-based paradigm involves setting up a dependency graph between your components - then telling your program which output you want, and letting it figure out what code to run. I'll given an introduction to the Luigi Python package and share my experiences how using Luigi has helped my team build operational data pipelines that are easy to develop locally, easy to parallelise, graceful when recovering from errors, and easy to extend.
Talk 2: Your name here? We are looking for a second speaker. Let me know if you are interested
Join us for a night of Python talks at the central Skyscanner office in Glasgow. We will have two talks. Skyscanner will be providing us with food and drinks.
Doors open at 17:30, please arrive by 18:30 at the latest.
Pizza will arrive at 18:00.
First talks will start at 18:30.
Talk 1: Flow-Based Programming with Luigi for doing Science
By: Harry Ambrose Jack
The Flow-based paradigm involves setting up a dependency graph between your components - then telling your program which output you want, and letting it figure out what code to run. I'll given an introduction to the Luigi Python package and share my experiences how using Luigi has helped my team build operational data pipelines that are easy to develop locally, easy to parallelise, graceful when recovering from errors, and easy to extend.
Talk 2: Data science version control with Python and DVC
By: Kristijan Ivancic
Software teams use version control systems like Git to collaborate on a shared codebase and keep track of changes. The workflows they use are now pretty standard. In the data science world, this is still an open problem. DVC is a tool that makes a solid attempt to tackle this issue. I'll show you how we use DVC to version our datasets and machine learning models, collaborate on projects that run Python code on large amounts of data, and make our experiments easily reproducible.
