Ask HN: Where to start learning about neural networks?
Hey HN,
I'm a high-level (language-wise) programmer, who is fascinated by the current developments in neural networks and deep learning. However, in a bid to understand more about this fascinating technology, I've realised that I have no idea about where to start leaning about neural nets.
I am certainly not hoping to (anytime soon) get to the point where I can build one myself, but would be hugely grateful if anybody with experience in the field could provide me with an overview or pointer of how to start getting into understanding deep learning, AI, and neural network.
Reading suggestions, article or even course links would be greatly helpful!
Cheers HN, and happy Sunday! ;)
5 comments
[ 2.3 ms ] story [ 20.3 ms ] threadSpeaking of which, while programming is a nice skill to have, most of the toughest bits of modern AI approaches, including neural networks, is in the maths. For neural nets, you need to have a solid understanding of multivariate calculus, statistical methods, and probability theory. You should have at least an intuition of what the error function is, and how error backpropagation works.
In my course, we used the Bishop book (Pattern Recognition and Machine Learning, https://books.google.com.au/books/about/Pattern_Recognition_...). It's dense, and very math-heavy, but it's definitely worth slogging through.
Once you're familiar with the basics, you can go deeper into the subject with the books suggested here.
[1]: https://www.coursera.org/learn/machine-learning
http://www.iro.umontreal.ca/~pift6266/H10/notes/mlintro.html
https://m.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ...