reinforcement_learning_course_materials
BestPractices
reinforcement_learning_course_materials | BestPractices | |
---|---|---|
1 | 1 | |
902 | 157 | |
0.4% | - | |
8.3 | 2.8 | |
12 days ago | 6 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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reinforcement_learning_course_materials
BestPractices
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Ideas for Materials Science / Data Science projects
My research group recently wrote the definitive best practice guide for getting into this field. We provide a GitHub with some example data that you could take a look at. The code snippets will be really useful because we have them really well commented. https://github.com/anthony-wang/BestPractices
What are some alternatives?
ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.
nbdev - Create delightful software with Jupyter Notebooks
learn-monogame.github.io - Documentation to learn MonoGame from the ground up.
fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
py - Repository to store sample python programs for python learning
LlamaIndex-course - Learn to build and deploy AI apps.
pymatgen - Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
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.
jupytemplate - Templates for jupyter notebooks
gds_env - A containerised platform for Geographic Data Science
jupyter-memgraph-tutorials - Learn to use Memgraph and GQLAlchemy quickly with the help of Jupyter Notebooks