Deep Learning

Deep learning is a subset of machine learning based on the artificial neural network based on human brain architecture. Deep Learning can be supervised, semi-supervised or unsupervised.

 

A basic deep learning model consists of four most important layers

1-Input Layer

2-Hidden Layer

3-Activation Function

4-Output Layer

 

Input and the hidden layer are nothing but just a collection of neurons that detects and accepts the input signals via sensors. And also Output layers are a collection of neurons that returns the output.

 

Most popular Deep learning architectures such as 

1-Artificial neural networks(ANN)

2-Recurrent neural networks (RNN)

3-Convolutional neural networks(CNN)

 

Application Area's of Deep Learning

computer vision, 

speech recognition, 

natural language processing, 

audio recognition, 

social network filtering, 

machine translation, 

bioinformatics,

etc...

In the upcoming articles, I will discuss each model in more depth.

Stay tuned for an article update.