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Ask HN: I'm 28. Is it too late to get started with AI/Machine Learning?
4 points by thakobyan on Oct 29, 2017 | hide | past | web | favorite | 3 comments
If no, what are the great resources for starters? Any tips before I get this journey going? Thank you.



It's never too late. Maybe apart from some age bias in the field (but that most occurs closer to 40). I would suggest starting with some good foundation in stats / modeling, this is an amazing book on that: An Introduction to Statistical Learning by Robert Tibshirani and Trevor Hastie.


No.

I recommend the ML course by Andrew Ng (I did it on coursera) and the AI course by Sebastian Thrun and Peter Norvig.


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:

http://ai.berkeley.edu/home.html

This class:

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

This class:

https://www.udacity.com/course/intro-to-machine-learning--ud...

This book:

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:

http://greenteapress.com/thinkstats/thinkstats.pdf

http://www.greenteapress.com/thinkbayes/thinkbayes.pdf

This book:

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.




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