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

Explore "Statistics" and "Probability Theory" Concepts and Their Implementations in "Python"

Applied Probability Theory for Everyone

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

🚀 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.

A Comprehensive AX = XB Calibration Solvers in Matlab

Common Code for Competitive Programming in C++

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

An open-source toolkit for entropic data analysis

Mathematical preliminaries for machine learning

The lecture notes for my discrete mathematics classes.

Interactive Mathematica notebooks illustrating the course content of VE401, Probabilistic Methods in Engineering at UM-SJTU Joint Institute.

Quizzes & Assignment Solutions for Data Science Math Skills on Coursera. Also included a few resources on side that I found helpful.

Probability Calculations with Random Numbers via Slot Machine Spin Simulation. Includes Probability Table and Results. Console App C#.

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