Machine Learning Using Python

MEAFA Professional Development Workshop

Welcome to the material page for the Machine Leaning section of the MEAFA professional development workshop on Machine Learning Using Python.


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.


Recommended reading

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.


Workshop Resources

Datasets for the Python section of the workshop

GitHub repository for Machine Learning Using Python


Day 3: Machine Learning Fundamentals

Session 1: Introduction to Machine Learning.

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Session 2: Regularised Linear Methods.

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Session 3: Naive Bayes.

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Session 4: Logistic Regression and Optimal Decisions.

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Day 4: Trees and Ensembles

Session 1: Decision Trees and Random Forests.

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Session 2: Boosting.

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Suggested reading: Introduction to Boosted Trees (from the XGBoost documentation).

Session 3: Ensemble Learning and Model Stacking.

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Session 4: Application.


Day 5: Support Vector Machines and Neural Networks

Session 1: Support Vector Machines

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Session 2: Getting Started with Neural Networks.

Session 3: Artificial Neural Networks.

Session 4: Introduction to Deep Learning.