SuperSuit
SuperSuit | kaggle-environments | |
---|---|---|
4 | 55 | |
432 | 273 | |
0.7% | 0.0% | |
8.0 | 6.4 | |
about 2 months ago | 1 day ago | |
Python | Jupyter Notebook | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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SuperSuit
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What is a wrapper in RL?
"SuperSuit is a library that includes all commonly used wrappers in RL (frame stacking, observation, normalization, etc.) for PettingZoo and Gym environments with a nice API. We developed it in lieu of wrappers built into PettingZoo. https://github.com/Farama-Foundation/SuperSuit "
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Simple (few states) two-agent environments?
+1 on PettingZoo, and the wrappers they provide as SuperSuit come in handy as well!. Also check out OpenSpiel
- Take a look at SuperSuit- It contains mature versions of all common preprocessing wrappers for gym environments, including ones that accept lambda functions for observations/actions/rewards
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Understanding multi agent learning in OpenAI gym and stable-baselines
Multi-agent isn’t supported by default in stable baselines, but you can make it work with PettingZoo. This example trains a single policy to control every agent in an environment (Parameter sharing). You could use these SuperSuit wrappers to work with other methods (self-play, independent learning, etc) but you would probably need to write some custom training code. https://github.com/PettingZoo-Team/SuperSuit#parallel-environment-vectorization
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.
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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-baselines - Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
docarray - Represent, send, store and search multimodal data
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
datasci-ctf - A capture-the-flag exercise based on data analysis challenges
dremio-oss - Dremio - the missing link in modern data
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows