pyroad
reinforcement_learning_course_materials
| pyroad | reinforcement_learning_course_materials | |
|---|---|---|
| 2 | 1 | |
| 305 | 902 | |
| - | 0.4% | |
| 2.5 | 8.3 | |
| about 1 year ago | 10 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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pyroad
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Is there anything similar to the Odin Project for Python?
There is a post from yesterday with a great roadmap. I saved the link, but not a post >_< https://github.com/amaargiru/pyroad
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Detailed Python developer roadmap
This article definitely contains mistakes and inaccuracies of different calibers, and of course, many required subsections are missing; so, if you notice any of these, feel free to comment, and if you feel the Force, you're welcome to fork the GitHub repository with the roadmap's source code and contribute whatever you feel is necessary; all corrections and additions are strongly encouraged. It also contains all the parts of the map in Mermaid diagram format, as well as png/svg illustrations.
reinforcement_learning_course_materials
What are some alternatives?
py4e - Web site for www.py4e.com and source to the Python 3.0 textbook
ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.
learn-monogame.github.io - Documentation to learn MonoGame from the ground up.
BestPractices - Things that you should (and should not) do in your Materials Informatics research.
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
LlamaIndex-course - Learn to build and deploy AI apps.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
gds_env - A containerised platform for Geographic Data Science
JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
ml-course - Open Machine Learning course
feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials
ppde642 - USC urban data science course series with Python and Jupyter