/zero-to-mastery-ml

All course materials for the Zero to Mastery Machine Learning and Data Science course.

Primary LanguageJupyter Notebook

Zero to Mastery Machine Learning

Binder Colab

Welcome! This repository contains all of the code, notebooks, images and other materials related to the Zero to Mastery Machine Learning Course on Udemy and zerotomastery.io.

Quick links

Updates

  • 12 October 2023 - Created an online book version of the course materials, see: https://dev.mrdbourke.com/zero-to-mastery-ml/ (currently a work in progress)
  • 7 Sep 2023 onward - Working on updating the materials for 2024, see the progress in #63
  • 25 Aug 2023 - Update section 3 end-to-end bulldozer regression notebook for Scikit-Learn 1.3+ (column order for predictions should match column order for training). See #62 for more.

What this course focuses on

  1. Create a framework for working through problems (6 step machine learning modelling framework)
  2. Find tools to fit the framework
  3. Targeted practice = use tools and framework steps to work on end-to-end machine learning modelling projects

How this course is structured

  • Section 1 - Getting your mind and computer ready for machine learning (concepts, computer setup)
  • Section 2 - Tools for machine learning and data science (pandas, NumPy, Matplotlib, Scikit-Learn)
  • Section 3 - End-to-end structured data projects (classification and regression)
  • Section 4 - Neural networks, deep learning and transfer learning with TensorFlow 2.0
  • Section 5 - Communicating and sharing your work

Student notes

Some students have taken and shared extensive notes on this course, see them below.

If you'd like to submit yours, leave a pull request.

  1. Chester's notes - https://github.com/chesterheng/machinelearning-datascience
  2. Sophia's notes - https://www.rockyourcode.com/tags/udemy-complete-machine-learning-and-data-science-zero-to-mastery/