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In this project, I’ve used Generative Adversarial Networks (GANs) to generate new images of human faces from scratch, based on the neural networks being trained on real human faces. I used the MNIST dataset and CelebFaces Attributes (CelebA) dataset in this project.
A Web Application Built with Flask and Python that reads images containing numbers with the Help of Tensor-flow should recognize each digit from 0 to 9
Leveraging the mapreduce paradigm we propose a solution to parallelize the feedforward operation of neural networks in order to speed it up for sufficiently large NN architectures and for sufficiently large datasets. Tested Using the MNIST dataset results can be found in the results.html and results.ipynb files.