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Deep Learning Concepts and Research Paper Implementations.

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DeepLearning

This repository contains the code for Deep Learning Concepts and Research Paper Implementations.

All code is written in Python 3 using PyCharm IDE.

Requirements

1. Python3.5 +

2. Numpy [+mkl for Windows]

3. Matplotlib

S.No. Project Name About Status
1. Basic Neural Network Implementation of a Basic Feed Forward Neural Network using Python and Numpy. Completed
2. Generative Adversarial Network (GAN) Implementation of Ian Goodfellow's Paper on GAN's. Completed
3. Artistic Style Transfer Implementation of Leon A Gaty's paper for Artifying Images. Completed
4. Recurrent Neural Network Implementation of a basic RNN using Python and Numpy. Completed
5. OpenAI Cart-Pole Game Bot Making a Neural Network learn how to play a Cart-Pole game by OpenAI and win it. Completed
6. AI Chatbot A chatbot that replies to Questions asked based on the Story/Text it has been Trained on. Completed
7. RNN Language Model A RNN model from scratch to show how Language Modelling is done. This code helps generate the new text with correct punctuations, starting and ending words etc. Completed
8. CNN Deep Layer Filters Visualization Implementation to Visualize the Deep Layer Filters of CNN using MNIST Dataset Completed
9. Deep Convolutional Generative Adversarial Network Implementation of DCGAN Paper for MNIST, CIFAR-10 and Celebrity Faces dataset. Ongoing
10. AutoEncoders [Linear, Convolutional, Variational] Implementation of Linear, Convolutional and Variational AutoEncoders. Ongoing
11. One Shot Learning with Memory Augmented Neural Networks Implementation of paper One Shot Learning with Memory Augmented Neural Networks [MANN]". Ongoing