Learn Machine Learning

Everyone in the world should have access to high-quality machine learning resources. This to empower Free and Open Machine Learning.

This blog is an excerpt of the FOSS ML Guide. An opinionated list of great open access machine learning learning resources. A lot of garbage is produced on the internet and even paid courses are often not good or simply learn you garbage.

This list of open (Creative Commons licensed ) machine learning training resources contains resources for starters who never want to do ‘hands-on’. But it contains also resources for experts to get better and better. Never stop learning.

Dive into Deep Learning

A great Interactive deep learning book with code, math, and discussions. Implemented with NumPy/MXNet, PyTorch, and TensorFlow.

Adopted at 175 universities from 40 countries.

Interpretable Machine Learning, A Guide for Making Black Box Models Explainable.

This book (cc-by-sa licensed) focuses on machine learning models for tabular data (also called relational or structured data) and less on computer vision and natural language processing tasks.

Other valuable open access ML resources:

  • Explainable Deep Learning: A Field Guide for the Uninitiated. Great learning guide for new and starting researchers in the Deep neural network (DNN) field. https://arxiv.org/pdf/2004.14545.pdf

  • Seeing Theory, A visual introduction to probability and statistics. Interactive learning book that visualizes the fundamental statistical concepts, https://seeing-theory.brown.edu/

Updates for this opinionated list of high quality open machine learning resources are welcome! Mail me or create an issue with your suggestion in the FOSS ML guide.