Write an efficient implementation of the logistic regression model trained by the SGD algorithm with momentum.

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The task is to train a binary classifier on a subset of the MNIST set, in which we distinguish classes (digits 0 and 1 are to be excluded from the set):

First numbers (2,3,5,7)

Compound numbers (4,6,8,9)

Write an efficient implementation of the logistic regression model trained by the SGD algorithm with momentum. You have to write the whole training process yourself, in Python language, using the library numpy. It is not allowed to use ready-made implementations of optimizers and models as well as libraries for automatic function differentiation (e.g. Tensorflow, pytorch, autograph).

Select hyperparameters in order to get the best possible result on the validation set. Draw and save conclusions from your experiments.

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