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I haven’t done the course, but +1 for the textbook. It’s freely downloadable and very readable. I learned a lot from it and the exercises are just the right l
by commandlinefan 7y ago
I haven’t done the course, but +1 for the textbook. It’s freely downloadable and very readable. I learned a lot from it and the exercises are just the right level of difficulty to help you really internalize the material. I wish there were self-check answers in the “back” of the book, though.
- rahimnathwani 7y agoThis book? http://www.mmds.org/ http://www.mmds.org/
- datlife 7y agoYes
- abhgh 7y agoYes this is a good book, esp. for an overview. At one time, I used to organize weekly discussion sessions at work based on sections in the book :-)
- commandlinefan 7y ago> for an overview I’ve read this before - that MMDS is more of a survey of machine learning’s “greatest hits” than a place to learn AI concepts. Out of curiosity, what would you recommend as something more beginner friendly?
- abhgh 7y agoI agree that MMDS is probably not a good introduction for ML- pretty idiosyncratic choice of topics for that. If you are fine with lectures, I always recommend Abu Mostafas lectures [1]; I think they have an extremely good balance of intuition and math, and I love his teaching style. Pretty underrated imho. Since these are a bit dated, they don't cover Deep Learning. For this, I like Andrew Ngs lectures [2]. Hugo Larochelle has a pretty extensive course on NNs too - I have viewed segments from it, and liked them[3]. Have heard good recommendations for fast.ai [4] if you need hands-on experience. [1] http://work.caltech.edu/lectures.html [2] sample playlist - https://www.youtube.com/watch?v=UNmqTiOnRfg&list=PLFKog8qYYq0Fs6lQf0jOuQD4XUQWYANPy [3] https://www.youtube.com/watch?v=SGZ6BttHMPw&list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH [4] https://www.fast.ai/