stable-baselines
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kaggle-environments | stable-baselines | |
---|---|---|
55 | 10 | |
274 | 4,000 | |
1.8% | - | |
6.6 | 0.0 | |
about 1 month ago | over 1 year ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | 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.
kaggle-environments
- Data Science Roadmap with Free Study Material
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Help needed! My first hackathon
If you are interested in Data Science, you may want to look at Kaggle competitions. https://www.kaggle.com/competitions
- What's a statistical / research methodology, that's not usually taught in grad programs, that you think more IO's should be aware about?
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Freaking out about how I’m inexperienced to land an internship and eventually a job
Secondly, if you feel like you do not have enough skills or a lack of practice answering problem statements, there are a lot of good websites where you can find interesting projects. I would recommend starting participating in some Kaggle competitions or download some free Google datasets and start playing with them.
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Capitalism provides half-assed solutions to extinction-level problems caused by capitalism
For reference: Kaggle is a Google product. You can see the list of current competitions here.
- Where can neural networks take me? - Semi-existential crisis
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What Can I Do With My Time as a Substitute for Strategy Computer Games?
You could try Kaggle competitions, or participating in forecasting markets (as you stated) is another option. You don't need any specific skill set to be a forecaster, the rules of the bet are stipulated and from there it's just based on your ability to predict the outcome. You could also try your hand at investing in the stock market, or try and make money betting on sports games. If you're very good at this stuff I'm sure you can make a lot of money doing it. The thing to keep in mind is that generally video games are much much easier than real life
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What is the best advanced professional certification for Data Science/ML/DL/MLOps?
As to the specifics of your projects, that's up to you. Try browsing Kaggle; check out some of the work we have on The Pudding; check out some journalism examples to see what you can try to build on or improve.
- Suggestions for projects on kaggle for cv?
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Hi! Im doing research on AI innovation. Does anybody know any specific platform where I can learn/understand and get case studies or on-going projects that companies are implementing? Thanks for your help!
You might want to look at kaggle competitions.
stable-baselines
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Distributed implementation tips
As underlined by gold-panda, you can give a try with multiprocessing. I once implemented a version based on what is done in stable_baselines v1 (https://github.com/hill-a/stable-baselines/blob/master/stable_baselines/common/vec_env/subproc_vec_env.py)
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GAIL without actions?
Found relevant code at https://github.com/hill-a/stable-baselines + all code implementations here
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Best framework to use if learning today
Depends what you wanna do. Universal answer would be https://stable-baselines.readthedocs.io/
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weird mean reward graph
As you will see here it is recommended to augment this safety measure with target kl_divergence, that will ensure even smoother learning and enforce early stopping to prevent learning collapses.
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Nvidia ISAAC gym/RL
Code for https://arxiv.org/abs/1707.06347 found: https://github.com/hill-a/stable-baselines
- Bounds for observation
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Understanding multi agent learning in OpenAI gym and stable-baselines
I haven't read the code, but stable-baselines doesn't support multi-agent environments (https://github.com/hill-a/stable-baselines/issues/423), so I think they're trying to make learning multi-agent easier with Environment.train().
- Using Reinforment Learning to beat the first boss in Dark souls 3 with Proximal Policy Optimization
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Reinforcement Learning Crash Course (Free)
- https://github.com/hill-a/stable-baselines (Tensorflow)
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JAX Implementations of Actor-Critic Algorithms
- tf2 speed: https://github.com/hill-a/stable-baselines/issues/576#issuecomment-573331715
What are some alternatives?
CKAN - CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers catalog.data.gov, open.canada.ca/data, data.humdata.org among many other sites.
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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.
docarray - Represent, send, store and search multimodal data
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
datasci-ctf - A capture-the-flag exercise based on data analysis challenges
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
dremio-oss - Dremio - the missing link in modern data
Tic-Tac-Toe-Gym - This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
DI-engine - OpenDILab Decision AI Engine