PyData Sydney’s March meetup featured presentations from two guest speakers: Nick Halmagyi and Zhuo Jia Dai. These presentations showcased two different areas of data science. Our session had a great turnout, and provided an opportunity for data enthusiasts to learn and network amongst their peers. To find the presentations from this session, please click here.
Below are the speakers’ summaries of their presentations.
Nick presented on Graph Analytics in Python:
Graph Analytics in Python: Predicting Missing Links
The goal of the missing link problem in graph theory is to predict the pairs of nodes, which are not currently linked, yet are most similar in character to existing links. It is a problem regularly studied by operators of social networks to suggest new connections between people but the only limit as to what can be represented as nodes and edges of a graph is your own creativity! The state of the art benchmarks are all rooted in machine learning and I will provide an example based exposition of how to approach this problem in Python.
Zhuo presented on Machine Learning in Banking:
Scorecards: How banks use Machine Learning to make lending decisions
Credit scoring has a long history in banking. Banks use it to make lending decisions on a daily basis. In this talk, ZJ will explain what a scorecard is, how is a scorecard built, and how modern ML frameworks, such as XGBoost, can be applied to automatically build scorecards.
Interested in taking the reins for the next PyData presentation? Want to teach your peers about the topic of your choice in the data science realm? Send us an email at email@example.com to enquire. Alternatively, please keep an eye on our Meetup page for more information about our next session in April.