Training Deep Neural Networks With Dropout

In this episode, we discuss the bane of many machine learning algorithms - overfitting. It is also explained why it is an undesirable way to learn and how to combat it via dropout.

The paper “Dropout: A Simple Way to Prevent Neural Networks from Overtting” is available here: https://www.cs.toronto.edu/~hinton/ab…

Andrej Karpathy’s autoencoder is available here: http://cs.stanford.edu/people/karpath…