BestPractices
machine-learning-experiments
BestPractices | machine-learning-experiments | |
---|---|---|
1 | 8 | |
155 | 1,602 | |
- | - | |
2.8 | 2.6 | |
6 months ago | 4 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
machine-learning-experiments
What are some alternatives?
nbdev - Create delightful software with Jupyter Notebooks
Torrent-To-Google-Drive-Downloader-v3 - Simple notebook to stream torrent files to Google Drive using Google Colab and python3.
fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
osumapper - An automatic beatmap generator using Tensorflow / Deep Learning.
py - Repository to store sample python programs for python learning
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
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.
PConv-Keras - Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
reinforcement_learning_course_materials - Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
lucid - A collection of infrastructure and tools for research in neural network interpretability.
jupytemplate - Templates for jupyter notebooks
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow