A neural network is a unit of deep learning, which itself is a sub-field of machine learning. A neural network refers to a series of algorithms that mimic the way a human brain operates to understand relationships between massive amounts of datasets.
What are the major types of neural networks?
Fully Connected Layer:
A fully connected layer connects each neuron in one layer to each neuron in the next layer.
A Convolution Layer is an essential type of layer in a CNN and is used for detecting features in images.
A Deconvolution Layer is a transposed convolution method that unsampled data to high resolution in an effective way.
A recurrent Layer has looping capacity. Its input comprises data for analysis plus output from the earlier calculation done by that layer.