Neural Nets Part 1

There is no known learning algorithm that is more flexible and powerful than the human brain. That's quite inspirational, if you think about it--to level up machine learning, maybe we should be going back to biology and letting millions of year of evolution guide the structure of our algorithms. 

This is the idea behind neural nets, which mock up the structure of the brain and are some of the most studied and powerful algorithms out there. In this episode, we’ll lay out the building blocks of the neural net (called neurons, naturally) and the networks that are built out of them. 

We’ll also explore the results that neural nets get when they're used to do object recognition in photographs.

Link: Lee, Grosse, Ranganath, Ng: Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations