Machine learning and deep learning are more or less on the same genre of machine learning algorithms but with a slight difference in the way they are being executed.
In the case of machine learning, what we do is that first of all we try to identify the defining features from the data set which correctly defines or classifies the data and this process are known as feature extraction.
What we do next is that we feed these features into our classification algorithms to train the machines in order to identify and predict the correct output.
Deep learning is a subset of machine learning where the feature extraction and classification is done simultaneously by the algorithm itself with the help of neural networks set for the particular purpose in the algorithm.
Deep learning is more influenced by the working of the human brains where the inputs are fed and the processing is done in the hidden neural layers and finally, the outputs are produced.
Deep learning algorithms have become more popular in case of image recognition, computer vision and natural language processing.
Artificial Neural Networks, Recurrent Neural Network and Convolution Neural Network have played a significant role in deep learning. Don’t worry if you don't know anything about these neural networks we will discuss this particular ANN, CNN and RNN separately.
