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
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
Comprehensive resources for data science interview preparation: assignments, math problems, logic tasks, live coding examples, and leetcode breakdowns.
Common Code for Competitive Programming in C++
📔 This repository is for storing my Higher Mathematics learning journey
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#.
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