Machine Learning Using Python
MEAFA Professional Development Workshop
- Setting up Python for the workshop
- Recommended reading
- Workshop resources
- Day 3: Machine Learning Fundamentals
- Day 4: Trees and Ensembles
- Day 5: Support Vector Machines and Neural Networks
Setting up Python for the workshop
Instructions for setting up a Python environment. Even though computers will be provided, you are highly encouraged to use your own laptop so that you are able to immediately continue working with these tools upon the conclusion of the workshop. We will provide assistance for the installation in the first day of the workshop, if you require it.
Installing additional Python packages. The workshop will rely on the additional machine learning and data visualisation packages listed here.
A Few Useful Things to Know About Machine Learning (Pedro Domingos). An overview of the essential lessons from applied machine learning. We will explore these concepts extensively in the workshop.
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (Aurélien Géron). My recommendation for those who would like to have a book reference for the topics covered in the workshop.
Day 3: Machine Learning Fundamentals
Session 1: Introduction to Machine Learning.
Session 2: Regularised Linear Methods.
Session 3: Naive Bayes.
Session 4: Logistic Regression and Optimal Decisions.
Day 4: Trees and Ensembles
Session 1: Decision Trees and Random Forests.
Session 2: Boosting.
Suggested reading: Introduction to Boosted Trees (from the XGBoost documentation).