Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Yt Channels Ds Ai Ml Cs | 1,084 | 6 months ago | ||||||||
A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep learning, Computer Science, programming, software engineering, etc. | ||||||||||
Ml University | 616 | a month ago | ||||||||
Machine Learning Open Source University | ||||||||||
A_journey_into_math_of_ml | 517 | 3 years ago | 12 | mit | Jupyter Notebook | |||||
汉语自然语言处理视频教程-开源学习资料 | ||||||||||
Mathematics_for_beginners | 482 | 4 years ago | 3 | |||||||
This is the formula sheet for "Mathematics for Beginners" by Siraj Raval on Youtube | ||||||||||
Convolutional_neural_network | 337 | 4 years ago | 7 | Jupyter Notebook | ||||||
This is the code for "Convolutional Neural Networks - The Math of Intelligence (Week 4)" By Siraj Raval on Youtube | ||||||||||
Lstm_networks | 176 | 4 years ago | 5 | Jupyter Notebook | ||||||
This is the code for "LSTM Networks - The Math of Intelligence (Week 8)" By Siraj Raval on Youtube | ||||||||||
Deep_q_learning | 156 | 5 years ago | 3 | Jupyter Notebook | ||||||
This is the Code for "Deep Q Learning - The Math of Intelligence #9" By Siraj Raval on Youtube | ||||||||||
Intro_to_the_math_of_intelligence | 153 | 4 years ago | 2 | mit | Python | |||||
This is the code for "Intro - The Math of Intelligence" by Siraj Raval on Youtube | ||||||||||
Recurrent_neural_network | 143 | 4 years ago | 2 | bsd-2-clause | Jupyter Notebook | |||||
This is the code for "Recurrent Neural Networks - The Math of Intelligence (Week 5)" By Siraj Raval on Youtube | ||||||||||
Machinelearning Deeplearning Code For My Youtube Channel | 119 | 7 days ago | 1 | Jupyter Notebook | ||||||
The full collection of all codes for my Youtube Channel segregated as per topic. |
This is the Code for "Deep Q Learning - The Math of Intelligence #9" By Siraj Raval on Youtube
This weeks challenge is to use Q learning to train an agent for any game you'd like. You can use OpenAI's Gym or Universe as a simulation testbed, but for the Q-Learning algorithm itself don't use any libraries. Bonus points if you use a deep convolutional network from scratch as well to learn from pixels, which means your agent is generalized to more than just one game (Deep Q Learning). Good luck!
This is the code for this video on Youtube by Siraj Raval as part of the Math of Intelligence series. We're going to rerecreate DeepMind's Deep Q Learner for a variety of games.
Use pip to install any dependencies.
Just run jupyter notebook
in terminal and the code will run. If you'd like to run this code on Super Mario, you need to install this additonal dependency.
The credit for this code goes to PeterWittek. I've merely created a wrapper to get people started.