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When I first read this paper, I found it to be immensely helpful. I'm new to Machine Learning but I was so inspired by this paper when I first found it that I wanted to build up resources around it.

Here's the result: https://github.com/hangtwenty/dive-into-machine-learning

I want this guide to be a good resource for other people like me, who are curious to get into Machine Learning by this process:

1) hacking 2) coming to understand what you hacked 3) more structured, in-depth learning

It can be intimidating to approach Machine Learning this way. For a long time it felt like I couldn't do steps 1 or 2... and had to start with 3. That's intimidating!

Pull requests welcome, I want this to be a good resource! Thanks all.



Well done - I'm sure this approach is helpful to many people who, like myself, learn best by using the process you summarised, so here's another compliment to the list :)


this is fantastic! I was looking for something like this to get started. Thank you so much for putting this together. I am taking some machine learning courses next semester and will use this to get familiar during the summer.


Really nice, thanks for posting.




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