Deep Learning is a branch of AI which uses Neural Networks for Machine Learning. In the recent years.
Deep Learning became a household name for AI engineers since 2012 when Alex Krizhevsky and his team won the ImageNet challenge. ImageNet is a computer vision competition in which the computer is required to correctly classify the image of an object into one of 1000 categories. The objects include different types of animals, plants, instruments, furniture, Vehicles to name a few.
This attracted a lot of attention from the Computer vision community and almost everyone started working on Neural Networks. But at that time, there were not many tools available to get you started in this new domain. A lot of effort has been put in by the community of researchers to create useful libraries making it easy to work in this emerging field. Some popular deep learning frameworks at present are Tensorflow, Theano, Caffe, Pytorch, CNTK, MXNet, Torch, deeplearning4j, Caffe2 among many others.