Last month, a video by 3Blue1Brown has been trending on YouTube, accumulating already over a quarter of a million views. It only lasts 10 minutes but provides a very good and intuitive explanation of the inner workings of Neural Networks (NN):
The Machine Learning & Deep Learning book I wrote about recently provides a more substantial explanation of the different NNs and their inner workings. Neural nets come in various different flavors and my list of Data Science, Machine Learning, & Statistics Resources includes useful cheatsheets and other information, such as the architecture map below.
If you still haven’t had enough, Daniel Shiffman demonstrates how to code Neural Networks in Processing (Java), and the video displays precisely what happens behind the scenes. Finally, MIT has made their AI course material open-source, and it includes two 45 minute lectures on NNs. The lecturing professor – Patrick Winston – isn’t much of a fan of these “bulldozer” algorithms. He has a stronger preference for “more sophisticated” mathematical learning through, for instance, Support Vector Machines.