xuefeng-xu's Stars
sympy/sympy
A computer algebra system written in pure Python
simd-everywhere/simde
Implementations of SIMD instruction sets for systems which don't natively support them.
chebfun/chebfun
Chebfun: numerical computing with functions.
dashingsoft/pyarmor
A tool used to obfuscate python scripts, bind obfuscated scripts to fixed machine or expire obfuscated scripts.
scikit-learn-contrib/imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
leanprover-community/mathlib4
The math library of Lean 4
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
krasserm/bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
AmazaspShumik/sklearn-bayes
Python package for Bayesian Machine Learning with scikit-learn API
skrub-data/skrub
Prepping tables for machine learning
epfml/OptML_course
EPFL Course - Optimization for Machine Learning - CS-439
Stirling-Tools/Stirling-PDF
#1 Locally hosted web application that allows you to perform various operations on PDF files
mpmath/mpmath
Python library for arbitrary-precision floating-point arithmetic
feature-engine/feature_engine
Feature engineering package with sklearn like functionality
pysathq/pysat
A toolkit for SAT-based prototyping in Python
apache/datasketches-cpp
Core C++ Sketch Library
apache/datasketches-python
Apache datasketches
amices/mice
Multivariate Imputation by Chained Equations
apache/madlib
Mirror of Apache MADlib
probml/pml-book
"Probabilistic Machine Learning" - a book series by Kevin Murphy
google-research/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
yuxiangw/autodp
autodp: A flexible and easy-to-use package for differential privacy
google/differential-privacy
Google's differential privacy libraries.
HIPS/autograd
Efficiently computes derivatives of NumPy code.
microsoft/prv_accountant
A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
jax-ml/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
google/rappor
RAPPOR: Privacy-Preserving Reporting Algorithms
tensorflow/privacy
Library for training machine learning models with privacy for training data
pytorch/opacus
Training PyTorch models with differential privacy
github/gitignore
A collection of useful .gitignore templates