nitrogenase

nitrogenase's Stars

• larsks/gitdriver

  Create a git repository from the revision history of a document in Google Drive.

  Language:Python13437

• alberti42/Volume-Control

  Successor of iTunes Volume Control

  Language:Objective-C21210

• dalcde/cam-notes

  My Cambridge Lecture Notes

  Language:TeX1.3k303

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 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, ... 🧠

  Language:Python55.8k5.7k

• 2anki/server

  Server to create Anki flashcards faster, easier and better today ⭐️

  Language:TypeScript30833

• gildas-lormeau/SingleFile

  Web Extension for saving a faithful copy of a complete web page in a single HTML file

  Language:JavaScript15.6k1k

• beardedspice/beardedspice

  Mac Media Keys for the Masses

  Language:Objective-C2.8k279

• alberti42/iTunes-Volume-Control

  Controlling iTunes and Spotify volume using volume up and volume down hotkeys.

  Language:Objective-C25418

• chemosim-lab/ProLIF

  Interaction Fingerprints for protein-ligand complexes and more

  Language:Python36870

• tobihol/zotero-mas-metadata

  A Zotero plugin that adds citation counts from Microsoft Academic to your references.

  Language:JavaScript657

• abudata/notes-on-python-tricks-the-book

  Notes I took while reading 'Python Tricks: The Book. A Buffet of Awesome Python Features'

  Language:Jupyter Notebook2031

• bslatkin/effectivepython

  Effective Python: Second Edition — Source Code and Errata for the Book

  Language:Python2.2k719

• jtleek/datasharing

  The Leek group guide to data sharing

  6.5k243k

• benedekrozemberczki/awesome-community-detection

  A curated list of community detection research papers with implementations.

  Language:Python2.3k362

• benedekrozemberczki/awesome-graph-classification

  A collection of important graph embedding, classification and representation learning papers with implementations.

  Language:Python4.8k742

• GLambard/AdamW_Keras

  AdamW optimizer for Keras

  Language:Python11433

• eriklindernoren/ML-From-Scratch

  Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

  Language:Python24k4.6k

• danijar/handout

  Turn Python scripts into handouts with Markdown and figures

  Language:Python2k106

• csurfer/blackcellmagic

  IPython magic command to format python code in cell using black.

  Language:Python30613

• chdoig/conda-auto-env

  Automatically activate a conda environment when entering a folder with an environment.yml file

  Language:Shell15245

• jupyterlab/jupyterlab-toc

  Table of Contents extension for JupyterLab

  Language:TypeScript727106

• chubin/cheat.sh

  the only cheat sheet you need

  Language:Python38.4k1.8k

• DeepGraphLearning/LiteratureDL4Graph

  A comprehensive collection of recent papers on graph deep learning

  3.1k564

• keras-team/keras-tuner

  A Hyperparameter Tuning Library for Keras

  Language:Python2.9k396

• songlab-cal/tape-neurips2019

  Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology. (DEPRECATED)

  Language:Python11834

• rasbt/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  Language:Jupyter Notebook16.7k4k

• facebookresearch/inversecooking

  Recipe Generation from Food Images

  Language:Python618149

• liyf1988/GHS

  Take Monte Carlo samples from the posterior distribution under the graphical horseshoe prior, to estimate the precision matrix for multivariate Gaussian data.

  Language:Matlab5

• hujie-frank/SENet

  Squeeze-and-Excitation Networks

  Language:Cuda3.4k840

• deepchem/DeepLearningLifeSciences

  Example code from the book "Deep Learning for the Life Sciences"

  Language:Jupyter Notebook354152