rlai
machine_learning_examples
| rlai | machine_learning_examples | |
|---|---|---|
| 1 | 3 | |
| 7 | 8,102 | |
| - | - | |
| 8.9 | 5.3 | |
| 22 days ago | 8 days ago | |
| Python | Python | |
| MIT License | - |
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rlai
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Python libraries for solving reinforcement learning problems implemented in OpenAI gym
I've worked through several OpenAI Gym environments with my RL library, which is based almost entirely on the RL textbook by Sutton and Barto (case studies here). No neural networks, nothing too fancy. But I do explore JAX for policy gradient methods / continuous control.
machine_learning_examples
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Doubt about numpy's eigen calculation
Does that mean that the example I found on the internet is wrong (I think it comes from a DL Course, so I'd imagine it is not wrong)? or does it mean that I am comparing two different things? I guess this has to deal with right and left eigen vectors as u/JanneJM pointed out in her comment?
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How to save an attention model for deployment/exposing to an API?
I've been following a course teaching how to make an attention model for neural machine translation, This is the file inside the repo. I know that I'll have to use certain functions to make the textual input be processed in encodings and tokens, but those functions use certain instances of the model, which I don't know if I should keep or not. If anyone can please take a look and help me out here, it'd be really really appreciated.
What are some alternatives?
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
d3rlpy - An offline deep reinforcement learning library
applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Coursera_Reinforcement_Learning - Coursera Reinforcement Learning Specialization by University of Alberta & Alberta Machine Intelligence Institute
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
neptune-client - 📘 The MLOps stack component for experiment tracking
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
dm_env - A Python interface for reinforcement learning environments
neptune-contrib - This library is a location of the LegacyLogger for PyTorch Lightning.