Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

Lecture notes on Bayesian deep learning

Rust for data analysis encyclopedia (WIP).

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

考研数学同济高等数学第七版线性代数浙大概率论

A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python

Unofficial solutions for Introduction to Probability, Second Edition by Joseph Blitzstein and Jessica Hwang.

Applied Probability Theory for Everyone

🚀 A library designed to facilitate work with probability, statistics and stochastic calculus

A quick introduction to all most important concepts of Probability Theory, only freshman level of mathematics needed as prerequisite.

Comprehensive resources for data science interview preparation: assignments, math problems, logic tasks, live coding examples, and leetcode breakdowns.

Chapter notes and exercise solutions for Reinforcement Learning: An Introduction by Sutton and Barto

An open-source toolkit for entropic data analysis

A Comprehensive AX = XB Calibration Solvers in Matlab

📔 This repository is for storing my Higher Mathematics learning journey

Common Code for Competitive Programming in C++

My solutions to Paul L. Meyer's "Introductory Probability and Statistical Applications, 2nd ed.", ISBN 0-201-04710-1.

Mathematical preliminaries for machine learning

The lecture notes for my discrete mathematics classes.

A math resource for CS student (I have decided to refactor the contents to my personal blog and continue working on this, so the project is archived)