Deep learning is an advanced field of Machine Learning that involves the analysis of input in a layering manner. This way each layer is used to extract deep information about the input provided to the learning model. 
With the help of Deep Learning, a large amount of data can be processed very smoothly. That is the reason for using deep learning algorithms for the analysis of unstructured data because the analysis of structured data doesn’t require much processing power, but for unstructured data, the deep learning algorithm works best. 
There are some topics that revolve around deep learning that include:

• ANN: It is called an Artificial Neural Network. ANN is the main approach of using deep learning. The ANN models are just like the human brain where the main role is of dendrites that receive and transmits the information using axons to other neurons. This way the information is processed among other neurons. 
• CNN: CNN stands for Convolutional Neural Network which is widely used for image and video recognition. The CNN is based on a mathematical concept which is similar to a multi-layer perceptron. CNN has three important layers that include Convolution, Pooling, and Fully Connected layers. 
• RNN: RNN is an abbreviation used for Recurrent Neural Network which is used to address the flaws that are found in other ANN models. The approach is mainly used in image classification.