Stars
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!
Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs/2002.08276
Self-study on Larry Wasserman's "All of Statistics"
A playbook for systematically maximizing the performance of deep learning models.
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
A collection of AWESOME things about domian adaptation
Pure Python implementation of machine learning algorithms
Statistical Rethinking course in pymc3
A list of awesome papers and cool resources on optimal transport and its applications in general! As you will notice, this list is currently mostly focused on optimal transport for machine learning…
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
Algorithms and data structures for preparing programming competitions: basic and advanced
The code for NeurIPS 2020 paper: Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion.
A simple Python debugger and profiler that generates animated visualizations of program flow, useful for algorithm learning.
❤️ 1000+ Hand-Crafted Go Examples, Exercises, and Quizzes. 🚀 Learn Go by fixing 1000+ tiny programs.
Computational Statistics and Statistical Computing
The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"
Seamless operability between C++11 and Python
分享 GitHub 上有趣、入门级的开源项目。Share interesting, entry-level open source projects on GitHub.
Curated list of project-based tutorials
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
100-Days-Of-ML-Code中文版
Quality control code for estimating the quality of the workers in crowdsourcing environments