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

Overview

Zero to Mastery Machine Learning

Binder Deepnote 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.

If you'd like to see anything in particular, please send me an email: [email protected] or leave an issue.

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/
Owner
Daniel Bourke
Machine Learning Engineer live on YouTube.
Daniel Bourke
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