Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

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• Updated Aug 22, 2026
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Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.

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• Updated Jul 18, 2026
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Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

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• Updated Mar 14, 2024

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

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• Updated Nov 20, 2024
• Jupyter Notebook

Data Science Roadmap from A to Z

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• Updated Dec 6, 2025

Powerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra

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• Updated Mar 9, 2026
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📙 The probability and statistics cookbook

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• Updated Feb 20, 2023
• TeX

The AI Compendium, previously called the ML Compendium, curates resources and explanations of machine learning (ML) and deep learning, from a business problem through data, AI, engineering, and product.

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• Updated Oct 1, 2026

The basic distribution probability Tutorial for Deep Learning Researchers

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• Updated Oct 1, 2020
• Python

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

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• Updated Nov 5, 2026

Self-study on Larry Wasserman's "All of Statistics"

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• Updated Dec 11, 2022
• Jupyter Notebook

Courses, Articles and many more which can help beginners or professionals.

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• Updated Dec 17, 2021

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

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• Updated Sep 18, 2022
• Jupyter Notebook

Teaching Materials for Dr. Waleed A. Yousef

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• Updated Jun 22, 2024
• Mathematica

All Stanford Cheatsheets: Artificial Intelligence, Transformers, LLMs, Deep Learning, Machine Learning, Probabilities, Statistics, Algebra and Calculus.

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• Updated Jan 6, 2026

Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes

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• Updated Jun 2, 2023
• Jupyter Notebook

Quantitative Interview Preparation Guide, updated version here ==>

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• Updated Mar 23, 2019
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VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers

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• Updated Sep 9, 2020

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

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• Updated Jul 10, 2023
• Jupyter Notebook

Algorithm is a library of tools that is used to create intelligent applications.

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• Updated Jan 17, 2020
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