My implementation of different neural network models from scratch in Python
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Single Layer Perceptron
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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
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assignment1: Implementing Single layer Perception
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assignment2: Implementing Hopfield network