INTRODUCTION
Deep Learning is a subset of machine learning which consists of a set of techniques based on Boltzmann machines and artificial neural networks. An artificial neural network (ANN) consists of layers-- input layer, hidden layers, and output layer. These layers are connected sequentially with each other through activation functions. In an ANN, if the number of hidden layers increases, the ANN is supposed to be a deeper and whole gamut of activities around deeper ANN are called Deep Learning.
A Deep Learning model can contain hidden layers as little as two to 20, 50, 100 or more. The art of obtaining an optimal number of hidden layers is the key to success in the model building with deep learning. To know detail about how deep learning works, you must read the free ebook (Written by Andrew Ng, MIT) by clicking following link---
www.deeplearningbook.org
