DeepLearning
fundamentalRL
Our great sponsors
| DeepLearning | fundamentalRL | |
|---|---|---|
| 1 | 1 | |
| 3 | 3 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 2 years ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DeepLearning
-
Help with my PyTorch implementation of PPO
I implemented PPO using PyTorch here. As is suggested, I was trying it on very simple environment (CartPole-v1).
fundamentalRL
What are some alternatives?
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
chainerrl - ChainerRL is a deep reinforcement learning library built on top of Chainer.
analisis-numerico-computo-cientifico - Análisis numérico y cómputo científico
cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
Deep-Learning-Experiments - Videos, notes and experiments to understand deep learning
weightless_NN_decompression - Proof of concept for neural network decompression without storing any weights
monodepth2 - [ICCV 2019] Monocular depth estimation from a single image
augmented-interpretable-models - Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
SeeAI - Enabling computers to perform NLP on data obtained from advanced computer vision
vision_models_playground - Playground for testing and implementing various Vision Models