PyData Kampala-a community of developers and users of open source data, science and engineering tools in Kampala invites you to its March Meetup to be hosted by the Makerere University Innovation Pod (Mak UniPod).
Date and Time: Friday 27th March 2026, 5:30 to 7:30 p.m. EAT prompt.
Speaker: Steven Kakaire, Software and Machine Learning Engineer
Topic: Systems Thinking and Data: Graphical Neural Networks (GNNs) and their applications.
Systems Thinking and Data: GNNs and their applications.
Financial Industry:
With multiple components and relations, financial data are often presented as graph data, since it could represent both the individual features and the complicated relations. Due to the complexity and volatility of the financial market, the graph constructed on the financial data is often heterogeneous or time-varying, which imposes challenges on modeling technology.
GNN models are able to handle the complex graph structure and achieve great performance and thus could be used to solve financial tasks.
In this tutorial, attendees shall learn the foundations of graph representation learning and their applications through use cases.
Registration: https://forms.gle/ewcqMW6pGR9qqzbR6
Speaker: Ahamada Shumuran, Intelligent Systems Architect, Ambassador, Alliance for AI, Makerere University
Topic: Predictive Models with Scikitlearn
In machine learning, where output often involve nonlinear functions, deep learning seeks to capture the complex relationships through muliticomputational layers. However, the underlying principles still rest on simple linear models. This hightlights the importance of understanding the theory and application of linear models as a basis of more advanced techniques.
In this talk, Ahamada shall highlight the practical application of regression algorithms, through a use case laying a foundation for understanding and applying more advanced ML algorithms.
To attend, you may register using the link: https://forms.gle/3Xg7TbP4Fgd5y8vD8
Online attedence: https://numfocus-org.zoom.us/j/87498088800?pwd=WpUbEbz5p6Gak6mslxeBbRrAxfDjfh.1