Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"
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Updated
Nov 12, 2022 - Jupyter Notebook
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
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.
Comprehensive resources for data science interview preparation: assignments, math problems, logic tasks, live coding examples, and leetcode breakdowns.
A Comprehensive AX = XB Calibration Solvers in Matlab
Common Code for Competitive Programming in C++
An open-source toolkit for entropic data analysis
📔 This repository is for storing my Higher Mathematics learning journey
Mathematical preliminaries for machine learning
The lecture notes for my discrete mathematics classes.
My solutions to Paul L. Meyer's "Introductory Probability and Statistical Applications, 2nd ed.", ISBN 0-201-04710-1.
A math resource for CS student
Quizzes & Assignment Solutions for Data Science Math Skills on Coursera. Also included a few resources on side that I found helpful.
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