Implement from scratch an RBM and apply it to DSET3. The RBM should be implemented fully by you (both CD-1 training and inference steps) but you are free to use library functions for the rest (e.g. image loading and management, etc.).
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Train an RBM with a number of hidden neurons selected by you (single layer) on the MNIST data (use the training set split provided by the website).
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Use the trained RBM to encode all the images using the corresponding activation of the hidden neurons.
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Train a simple classifier (e.g. any simple classifier in scikit) to recognize the MNIST digits using as inputs their encoding obtained at step 2. Use the standard training/test split. Show a performance metric of your choice in the presentation/handout.