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Ask HN: I'm 28. Is it too late to get started with AI/Machine Learning?
If no, what are the great resources for starters? Any tips before I get this journey going? Thank you.
- shock 9y agoNo. I recommend the ML course by Andrew Ng (I did it on coursera) and the AI course by Sebastian Thrun and Peter Norvig.
- matchmike1313 9y agoIt'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.
- mindcrime 9y agoWhat? 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 http://ai.berkeley.edu/home.html This class: https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning This class: https://www.udacity.com/course/intro-to-machine-learning--ud120 https://www.udacity.com/course/intro-to-machine-learning--ud... This book: https://www.amazon.com/Artificial-Intelligence-Modern-Approach-3rd/dp/0136042597 https://www.amazon.com/Artificial-Intelligence-Modern-Approa... This book: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1491962291/ref=sr_1_3?s=books&ie=UTF8&qid=1509309023&sr=1-3 https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-T... This book: https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/ref=sr_1_5?s=books&ie=UTF8&qid=1509309023&sr=1-5 https://www.amazon.com/Introduction-Machine-Learning-Python-... These books: http://greenteapress.com/thinkstats/thinkstats.pdf http://greenteapress.com/thinkstats/thinkstats.pdf http://www.greenteapress.com/thinkbayes/thinkbayes.pdf http://www.greenteapress.com/thinkbayes/thinkbayes.pdf This book: https://www.amazon.com/Machine-Learning-Hackers-Studies-Algorithms/dp/1449303714 https://www.amazon.com/Machine-Learning-Hackers-Studies-Algo... This book: https://www.amazon.com/Thoughtful-Machine-Learning-Test-Driven-Approach/dp/1449374069 https://www.amazon.com/Thoughtful-Machine-Learning-Test-Driv... These subreddits: http://artificial.reddit.com http://artificial.reddit.com http://machinelearning.reddit.com http://machinelearning.reddit.com http://semanticweb.reddit.com http://semanticweb.reddit.com These journals: http://www.jmlr.org http://www.jmlr.org http://www.jair.org http://www.jair.org This site: http://arxiv.org/corr/home/ 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 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.