Thoughtful Machine Learning: A Test-Driven Approach

Category: Computer Science
Author: Matthew Kirk
3.1
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Comments

by mindcrime   2017-10-31
What? No. Why in the world do people even ask this kind of question. To a first approximation, the answer to "is it too late to get started with ..." question is always "no".

If no, what are the great resources for starters?

The videos / slides / assignments from here:

https://www.amazon.com/Artificial-Intelligence-Modern-Approa...

This book:

https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-T...

This book:

https://www.amazon.com/Introduction-Machine-Learning-Python-...

These books:

https://www.amazon.com/Machine-Learning-Hackers-Studies-Algo...

This book:

https://www.amazon.com/Thoughtful-Machine-Learning-Test-Driv...

These subreddits:

http://artificial.reddit.com

http://machinelearning.reddit.com

http://semanticweb.reddit.com

These journals:

http://www.jmlr.org

http://www.jair.org

This site:

http://arxiv.org/corr/home/

Any tips before I get this journey going?

Depending on your maths background, you may need to refresh some math skills, or learn some new ones. The basic maths you need includes calculus (including multi-variable calc / partial derivatives), probability / statistics, and linear algebra. For a much deeper discussion of this topic, see this recent HN thread:

https://news.ycombinator.com/item?id=15116379

Luckily there are tons of free resources available online for learning various maths topics. Khan Academy isn't a bad place to start if you need that. There are also tons of good videos on Youtube from Gilbert Strang, Professor Leonard, 3blue1brown, etc.

Also, check out Kaggle.com. Doing Kaggle contests can be a good way to get your feet wet.

And the various Wikipedia pages on AI/ML topics can be pretty useful as well.