Sign up at https://bit.ly/hs-2019-ml
Machine Learning is gaining increased traction in the technology scene. This workshop will introduce you to a powerful yet simple classification model, based on the well-known Bayes’ Theorem, which is extensively used in text classification like detecting spam email.
Here's an outline of the workshop:
1. Setup (5mins)
2. Intro talk (30mins)
3. Coding on discretisation/structure learning (20mins)
4. Talk on findings from structure learning + probability fitting (15mins)
5. Coding on probability fitting (15mins)
6. Talk on findings from probability fitting + inference/interventions (15mins)
7. Coding on inference/interventions (15mins)
8. Close (10mins)
Workshop is open to the public, and basic Python knowledge is required. You're required to have Jupyter notebook and Python installed on your computers, and remember to bring a fully charged laptop as power points may be limited.
Speaker profile: Paul Beaumont is a Senior Data Scientist at QuantumBlack. He works on statistical models for explanatory, predictive and prescriptive problems, and his role involves designing mathematical models to help clients understand pertinent questions about their data. Paul holds a PhD in Mathematics & Computer Science, and leads QuantumBlack’s R&D efforts in Causal Inference.