Deep Learning and its Applications using Python

1Introduction to Deep Learning

The deep learning history is often tracked back to 1943 when Walter Pitts and Warren McCulloch computed a model (computer model) which support the human brain (the neural networks). To mimic the thought process of human, they used a collection of algorithms and arithmetic concepts which is called as threshold logic. Since 1943, Deep learning [1] is evolving without break. As it utilizes multiple algorithm in multiple layers to mimic the thought process by processing the data, understanding the human speech and visually recognizing objects. Here the information is processed by passing it into multiple layers, where each layer’s output act as an input for the next layer. The first layer in a network is called the input layer, while the last is called an output layer. All the layers between the two are referred to as hidden layers. Each layer is typically a simple, uniform algorithm containing one kind of activation function. Deep learning’s other aspect is feature extraction. It uses an algorithm to automatically construct meaningful “features” from the data which will be used for training, learning, and understanding. Mostly, a data scientist, or a programmer, is responsible for this process.

1.1 History of Deep Learning

Right now, the world is seeing a global Artificial Intelligent revolution across all industry with the driving factor as deep learning. Google and Facebook using deep learning now, and it has not appeared overnight, rather it ...