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Top 4 Jupyter Notebook Ray Projects
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Project mention: Ask HN: Daily practices for building AI/ML skills? | news.ycombinator.com | 2023-12-14
coming from a similar context, i believe going top down might be the way to go.
up to your motivation, doing basic level courses first (as shared by others) and then tackling your own application of the concepts might be the way to go.
i also observe the need for strong IT skills for implementing end-to-end ml systems. so, you can play to your strenghts and also consider working on MLOps. (online self-paced course - https://github.com/GokuMohandas/mlops-course)
i went back to school to get structured learning. whether you find it directly useful or not, i found it more effective than just motivating myself to self-learn dry theory. down the line, if you want to go all-in, this might be a good option for you too.
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Project mention: A comprehensive guide to building RAG-based LLM applications for production | news.ycombinator.com | 2023-10-25
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gym-continuousDoubleAuction
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
Jupyter Notebook Ray discussion
Jupyter Notebook Ray related posts
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A comprehensive guide to building RAG-based LLM applications for production
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gym-continuousDoubleAuction: NEW Deep Learning And Reinforcement Learning - star count:104.0
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gym-continuousDoubleAuction: NEW Deep Learning And Reinforcement Learning - star count:104.0
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gym-continuousDoubleAuction: NEW Deep Learning And Reinforcement Learning - star count:104.0
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gym-continuousDoubleAuction: NEW Deep Learning And Reinforcement Learning - star count:104.0
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A note from our sponsor - SaaSHub
www.saashub.com | 10 Oct 2024
Index
What are some of the best open-source Ray projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | Made-With-ML | 37,193 |
2 | mlops-course | 2,838 |
3 | llm-applications | 1,682 |
4 | gym-continuousDoubleAuction | 138 |