Firstly a big applause and immense appreciation for Jeremy, Rachel and the Fastai Team for demystifying the common phrase "black box" and provide such great content as a MOOC. If you haven't already checked out Fastai , i would urge you to click on the link before proceeding further.
I would be justified to say that this is one of the best ML course for programmers. There are two sides of learning ML: 1. Theory 2. Practical, while the former is much required it's oft better to get your hands dirty and start with the latter and learn the former as required. While there are many other resources and notes for this course(mentioned below), this is what i learnt from the course.
Github Repository
Videos
Notes
Forums for doubts
Have included a document for cloning Fastai through git.
Note:
- Have used the fastai-cpu version. All the codes are reproduced from the Fastai ML course.
- For better readability, please use the notebooks with "Collapsible Headings" extension from Jupyter Nbextensions