Open Tech Calendar

Embark on a captivating exploration of the intricate world of machine learning as we delve into the realms of End-to-End development using Python, with a particular focus on Linear and Logistic Regression. In this enlightening talk, we will navigate through the captivating landscape of Exploratory Data Analysis (EDA) and the application of these fundamental regression models. Prepare to unravel the secrets hidden within your datasets as we unravel the power of EDA, illuminating patterns and insights that lay the foundation for robust Machine Learning models. Whether you are a novice or a seasoned practitioner, this session promises to be an insightful journey, offering practical tips and strategies for effective feature analysis, data preprocessing, and visualizations.The heart of our discourse will pulsate with the rhythm of Linear and Logistic Regression, two pillars of supervised learning. Discover how these models elegantly capture relationships within data, making them invaluable tools for prediction and classification tasks. Engage in hands-on demonstrations as we navigate Python's data science ecosystem, showcasing the seamless integration of scikit-learn for model development.Join in demystifying the complexities of End-to-End Machine Learning, where we harmonize data exploration and model building into a symphony of intelligence. By the end of this talk, you'll not only grasp the intricacies of Linear and Logistic Regression but also gain a holistic understanding of the entire machine learning pipeline, empowering you to orchestrate your own data symphony.


Bio: Gbenga Ayelabola, an accomplished data analytics consultant and passionate problem solver, brings nearly a decade of diverse data expertise to the table. With a background in Computer Science, Gbenga has made significant contributions across healthcare, consulting, and EduTech industries. He has provided training to over 200 professionals across the UK in various Data Analytics tracks. His proficiency extends to various facets of data, including analysis, modelling, transformation, strategic planning, and management. Gbenga excels in stakeholder management, KPI definition, and the design of impactful dashboards and reports. His skills also encompass the application of Machine Learning for predictive insights. Currently working with Multiverse as a Data Fellowship Coach, he dedicates his efforts to guiding and shaping the future of data leaders. Gbenga's dynamic career is marked by a commitment to excellence, making him a standout figure in the evolving realms of data analytics and leadership.

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