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This repository contains python code for doing linear regression in two variables.
This repository contains code for classification of MNIST dataset using a very simple neural network. The code has been done in python using numpy. Since this is a very light network, the classification accuracy is around 92% on average. The output layer is a softmax layer, the activation function used is sigmoid and the loss function is cross entropy loss.
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