Keep_it_simple
Codebase, data and models for the Keep it Simple paper at ACL2021
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Awesome Artificial Intelligence | 8,777 | 3 months ago | 48 | |||||||
| A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers. | ||||||||||
| Complete Life Cycle Of A Data Science Project | 499 | 4 months ago | 4 | mit | ||||||
| Complete-Life-Cycle-of-a-Data-Science-Project | ||||||||||
| Free Ai Resources | 466 | 4 months ago | 16 | mit | ||||||
| 🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone! | ||||||||||
| Pytorch Vsumm Reinforce | 342 | 2 years ago | 51 | mit | Python | |||||
| Unsupervised video summarization with deep reinforcement learning. AAAI'18. | ||||||||||
| Flappy Es | 140 | 2 years ago | Python | |||||||
| Flappy Bird AI using Evolution Strategies | ||||||||||
| Python Machine Learning Book 3rd Edition | 93 | 6 months ago | 2 | mit | Jupyter Notebook | |||||
| <머신 러닝 교과서 3판>의 코드 저장소 | ||||||||||
| Sutton Barto Rl Exercises | 83 | 4 months ago | Jupyter Notebook | |||||||
| 📖Learning reinforcement learning by implementing the algorithms from reinforcement learning an introduction | ||||||||||
| Dads | 82 | 4 years ago | 1 | apache-2.0 | Python | |||||
| Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control. | ||||||||||
| Machinelearningwithpython | 79 | 2 years ago | Jupyter Notebook | |||||||
| Get started with Machine Learning with Python - An introduction with Python programming examples | ||||||||||
| Goneat | 69 | 3 | 6 months ago | 23 | November 13, 2023 | 10 | mit | Go | ||
| The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation | ||||||||||
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