PyDataMCR December

PyDataMCR December Talks

Continuing with some more great talks we are hosted this month by Krakenflex.

THE TALKS

Beyond Traditional Recommenders: Leveraging Graph Neural Networks for Food Delivery Platforms - Chris Dambamuromo (he/him)

In this talk, Chris will demonstrate how to implement a Graph Neural Network (GNN) based recommendation system for food delivery platforms. Drawing from real-world examples, he'll explore how GNNs can effectively balance the complex dynamics of a three-sided marketplace - customers, restaurants, and delivery partners. The presentation will cover practical aspects of working with limited data, implementing GraphSAGE, and handling multiple optimisation objectives. This independent project represents his exploration of recommendation systems and graph-based machine learning, bringing together his technical expertise and interest in practical AI applications.

Chris is a Data Engineer with over a decade of software development experience, specialising in data engineering and machine learning. With a background in Applied Mathematics and Intelligent Computer Systems, he's passionate about applying advanced AI techniques to solve real-world problems. Currently focusing on recommendation systems and graph-based machine learning, Chris brings practical insights from his experience in both software development and data engineering.

The talk will include code examples and is suitable for data scientists, ML/Data engineers, and anyone interested in practical applications of Graph Neural Networks.

Building Seamless Pipelines with DBT and Python - Andy Stafford Hughes (he/him)

I will discuss how we successfully automated testing with DBT and Python in our Data Products team.

Andrew is an Enterprise Data & AI Test Architect with extensive experience in quality assurance across industries like healthcare, gaming, and retail. Currently at AstraZeneca, he is enhancing test automation frameworks for data science and GenAI projects while mentoring teams to improve their automation testing capabilities globally.

LOCATION
We'll be at Krakenflex, who are also kindly supplying catering. The capacity is limited to 90.

After the talks we'll all head somewhere local for some post-event socialising.

EVENT GUIDELINES
PyDataMCR is a strictly professional event, as such professional behaviour is expected.

PyDataMCR is a chapter of PyData, an educational program of NumFOCUS and thus abides by the NumFOCUS Code of Conduct

https://pydata.org/code-of-conduct.html

Please take a moment to familiarise yourself with its contents.

ACCESSIBILITY
Under 16s welcome with a responsible guardian. There is a quiet room available if needed. Toilets are accessible.

SPONSORS
Thank you to NUMFocus for sponsoring Meetup and further support
Thank you to AutoTrader for sponsoring PyDataMCR.
Thank you to Krakenflex for sponsoring PyDataMCR, as well as hosting this event!