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1. PromixalPolicyOptimization PromixalPolicyOptimization Public

   Proximal Policy Optimization using Pytorch and the Unity Reacher environment.

   Python 1

2. MultiAgentDDPG MultiAgentDDPG Public

   Multi Agent DDPG implementation in Python3 and Pytorch

   Python 1 2

3. deep-q-bananacollector deep-q-bananacollector Public

   With this you can train an agent to navigate and collect bananas in a large, square world.

   Jupyter Notebook 1

4. This gist contains a list of importa... This gist contains a list of important points from fast.ai "practical deep learning for coders" and "cutting edge deep learning for coders" MOOC

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   This gist contains a list of points I found very useful while watching the fast.ai "Practical deep learning for coders" and "Cutting edge deep learning for coders" MOOC by Jeremy Howard and team. This list may not be complete as I watched the video at 1.5x speed on marathon but I did write down as many things I found to be very useful to get a model working. A fair warning the points are in no particular order, you may find the topics are all jumbled up.

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   Before beginning, I want to thank Jeremy Howard, Rachel Thomas, and the entire fast.ai team in making this awesome practically oriented MOOC.

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   1. Progressive image resolution training: Train the network on lower res first and then increase the resolution to get better performance. This can be thought of as transfer learning from the same dataset but at a different resolution. There is one paper by NVIDIA as well that used such an approach to train GANs. 

5. deep_learning_and_the_game_of_go deep_learning_and_the_game_of_go Public

   Forked from maxpumperla/deep_learning_and_the_game_of_go

   Code and other material for the book "Deep Learning and the Game of Go"

   Python

6. DL_PyTorch DL_PyTorch Public

   Forked from udacity/DL_PyTorch

   Code for the Deep Learning with PyTorch lesson

   Jupyter Notebook