The third task is about classifying Fashion-MNIST dataset. A short description of the dataset is provided in the Datasets section above.

INSTRUCTIONS TO CANDIDATES

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Make this code run properly in the Main Function.Ayttached file is a jupter notebook. Problem is to create a artificial neural network with backprobocation from first principles using only python and numpy and pandas.

 

 

The third task is about classifying Fashion-MNIST dataset. A short description of the dataset is provided in the Datasets section above.

You can use other API’s/libraries for loading the dataset, but not for the neural network implementation. The point of this task is to develop a multi-layer neural network for classification using mostly the numpy.

- Implement sigmoid and Relu layers (with forward and backward pass)(10%)

- Implement a softmax output layer(10%)

- Implement a fully parameterizable neural network (number and types of layers, number of units can - be changed)(20%)

- Implement an optimizer (e.g. SGD or Adam) and a stopping criterion of your choosing(10%)

- Train your Neural Network using backpropagation(20%)

- Evaluate different neural network architectures/parameters, present and discuss your results

Attachments:

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