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updated deep learning.md

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Bin Yang
2021-03-31 23:55:42 -04:00
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| repo | comment | created_at | last_commit | star_count | repo_status | rating |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|:--------------------------|:------------------|:---------------------------------------------------------------------|:--------------------|
| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>528.0</sub> | <sub>![active](https://placehold.it/15/00FF00/000000?text=+)</sub> | <sub>:star:x4</sub> |
| | Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | | | | | |
| <sub>[awesome-deep-trading](https://github.com/cbailes/awesome-deep-trading)</sub> | <sub>curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes</sub> | <sub>11/26/18 3:23</sub> | <sub>1/1/21 9:41</sub> | <sub>528.0</sub> | <sub>![active](https://placehold.it/15/00FF00/000000?text=+)</sub> | <sub>:star:x4</sub> |
| <sub>[trading-bot](https://github.com/pskrunner14/trading-bot)</sub> | <sub>Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python </sub> | <sub>8/13/18 10:44</sub> | <sub>1/23/20 4:41</sub> | <sub>285.0</sub> | <sub>![active](https://placehold.it/15/00FF00/000000?text=+)</sub> | <sub>:star:x3</sub> |
| <sub>[Advanced-Deep-Trading](https://github.com/Rachnog/Advanced-Deep-Trading)</sub> | <sub>notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include [mlfinlab](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/shap) for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. </sub> | <sub>2/16/19 21:18</sub> | <sub>11/29/20 20:12</sub> | <sub>319.0</sub> | <sub>![active](https://placehold.it/15/00FF00/000000?text=+)</sub> | <sub>:star:x3</sub> |
| <sub>[deep-RL-trading](https://github.com/golsun/deep-RL-trading)</sub> | <sub>NEW</sub> | <sub>2/25/18 17:41</sub> | <sub>12/1/20 22:06</sub> | <sub>231.0</sub> | <sub>![active](https://placehold.it/15/00FF00/000000?text=+)</sub> | <sub>:star:x3</sub> |