My implementation of different neural network models from scratch in Python

• Single Layer Perceptron

• HopField Network

It's part in the Nerual Networks, which says whether the neuron should be active or not.

• Sigmoid

It is a characteristic S-shaped function; the domain of the function is R, which maps to a range of [0, 1], also called a logistic function.

• ReLU

It is a piecewise function, which outputs the number itself if +ve else 0.

• Softmax

It's a mathematical function which gives a normalized exponential vector of n-input vector, which is probabilistic distribution.

Check the readme's in the directories for more description

• assignment1: Implementing Single layer Perception

• assignment2: Implementing Hopfield network