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Top 23 Jupyter Notebook reinforcement-learning Projects
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nn
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
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FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
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InfluxDB
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amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
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Reinforcement-Learning
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning (by andri27-ts)
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alpha-zero-general
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
Solutions of Reinforcement Learning, An Introduction
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tensor-house
A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
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TextWorld
TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
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TradeMaster
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:
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Hands-On-Meta-Learning-With-Python
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
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Popular-RL-Algorithms
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
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reinforcement_learning_course_materials
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
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rliable
[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.
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SaaSHub
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Project mention: GPT-4, without specialized training, beat a GPT-3.5 class model that cost $10B | news.ycombinator.com | 2024-03-24There is also the open source FinGPT, that is claimed to beat GPT4 in some benchmarks at a fine tuning cost of $17.25.
https://github.com/AI4Finance-Foundation/FinGPT
I need to use AWS Sagemaker (required, can't use easier services) and my adviser gave me this document to start with: https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_langchain_jumpstart.ipynb
Project mention: Competitive reinforcement learning for turn-based games | /r/reinforcementlearning | 2023-05-26This is a good intro to alphazero and montecarlo treesearch , Followed by This repo.
For note-taking specifically, I've tried everything from plain old pen and paper to more modern solutions like Evernote and emacs (if you can call that modern), but nothing I've come across really beats Anki.
Although its main selling point is as a program for flashcards with spaced repetition, it comes with pretty much all the features of a good note-taking app, like tags, easy to organize, synchronization across devices (you can set up your own server), good interface for searching through your notes (which are stored in an Sqlite db if that matters), and yes, LaTeX. Not only that, it's also highly extendable with third-party plugins, so if there are features that you miss chances are there's a plugin for it. In other words, you can use it perfectly fine just taking notes. However, where it really shines is in all of this in combination the spaced repetition algorithm, which is now on steroids with FSRS[1][2]. The downside is that for this to be effective for the things you want to memorize, you'll have to write your notes to be suitable for a flashcard, but if you do it consistently you'll soon notice that you can store most of your notes in your head (needless to say, any student would greatly benefit from this). Now, if that's too much work, you can still just use the scheduling to have it remind you of your notes. Either way, even as someone who sometimes goes out of his way to shoehorn everything into Emacs, I can't see a reason not to use anki for note-taking.
[1]https://github.com/open-spaced-repetition/fsrs4anki/blob/mai...
[2]https://www.youtube.com/watch?v=OqRLqVRyIzc
Project mention: TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0 | /r/algoprojects | 2023-12-09
Project mention: trading-bot: Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper py | /r/algoprojects | 2023-12-10
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook reinforcement-learning related posts
- trading-bot: Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper py
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
- TradeMaster: NEW Deep Learning And Reinforcement Learning - star count:910.0
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www.influxdata.com | 26 Apr 2024
Index
What are some of the best open-source reinforcement-learning projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | nn | 48,004 |
| 2 | FinGPT | 11,419 |
| 3 | amazon-sagemaker-examples | 9,491 |
| 4 | TensorFlow-Tutorials | 9,250 |
| 5 | Practical_RL | 5,709 |
| 6 | Reinforcement-Learning | 4,091 |
| 7 | alpha-zero-general | 3,667 |
| 8 | Andrew-NG-Notes | 2,228 |
| 9 | fsrs4anki | 2,177 |
| 10 | brax | 2,058 |
| 11 | ml-course | 2,039 |
| 12 | Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions | 1,793 |
| 13 | tensor-house | 1,162 |
| 14 | TextWorld | 1,150 |
| 15 | TradeMaster | 1,129 |
| 16 | Hands-On-Meta-Learning-With-Python | 1,123 |
| 17 | Popular-RL-Algorithms | 981 |
| 18 | hands-on-rl | 960 |
| 19 | reinforcement_learning_course_materials | 900 |
| 20 | trading-bot | 871 |
| 21 | rl_games | 723 |
| 22 | gdrl | 699 |
| 23 | rliable | 698 |
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