10 Free Online Courses on Machine Learning

1. Probability and Statistics by Stanford Online This self-paced course covers basic concepts in probability and statistics spanning over four fundamental aspects of machine learning: exploratory data analysis, producing data, probability, and inference.
https://online.stanford.edu/courses/gse-yprobstat-probability-and-statistics

 

2. Linear Algebra by MIT Hands down the best linear algebra course I’ve seen, taught by the legendary professor Gilbert Strang.
 https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

 3. CS231N: Convolutional Neural Networks for Visual Recognition by Stanford Theories are balanced with practices. The notes are well written with visualizations that explain difficult concepts e.g. backprop, losses, regularizations, dropouts, batchnorm
https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq

4. Practical Deep Learning for Coders by fastai This hands-on course focuses on getting things up and running. It has a forum with helpful discussions about the latest best practices in ML. By

@jeremyphoward and @math_rachel

 https://course.fast.ai/

 

5. CS224N: Natural Language Processing with Deep Learning by Stanford A must-take course for anyone interested in NLP. The course is well organized, well taught, and up-to-date with the latest research. Taught by the amazing @chrmanning

 

 https://www.youtube.com/playlist?list=PLU40WL8Ol94IJzQtileLTqGZuXtGlLMP_

 

 6. Machine Learning by Coursera Originally taught at Stanford, Andrew Ng’s course is probably the most popular machine learning course in the world. Its Coursera version has been enrolled by more 2.5M people as of writing.

https://www.coursera.org/learn/machine-learning

 

7. Probabilistic Graphical Models Specialization by Coursera Unlike most AI courses that introduce small concepts one by one, this tackles AI top-down as it forces you to think about what exactly you're trying to learn when you say ML. By @DaphneKoller

 

 https://www.youtube.com/watch?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ&v=2pWv7GOvuf0

 

8. Introduction to Reinforcement Learning by DeepMind RL is hard, but David Silver is here to the rescue. This course provides a great introduction to RL with intuitive explanations and fun examples, taught by one of the world’s leading experts.

 

 

9. Full Stack Deep Learning Bootcamp Most courses only teach you how to train and tune your models. This is the only one I've seen that shows you how to design, train, and deploy models from A to Z. By

@pabbeel ,  @josh_tobin_ @sergeykarayev

 

 https://fullstackdeeplearning.com/march2019

 

 

10. How to Win a Data Science Competition: Learn from Top Kagglers by Coursera Time to head over to Kaggle to get some experiences building a machine learning for your resume and make some $$$

https://www.coursera.org/learn/competitive-data-science/home/welcome