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
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
Math Parser: Java, C#, C++, Kotlin, Android, and all .NET platforms (Nuget, Maven, CMake). Supports .NET Framework, .NET Core, .NET Standard, Xamarin, and more. Features: rich built-in library of math functions, operators, constants. Flexible in user-defined arguments, functions. Expressions provided as plain text. Easy to use. Well documented.
Forward Mode Automatic Differentiation for Julia
New open-source cross-platform symbolic algebra library for C# and F#. Can be used for both production and research purposes.
Quantitative Interview Preparation Guide, updated version here ==>
The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI
Do maths like a normal person
a symbolic math expression evaluator for javascript
Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
➗ A really micro micro-service for advanced math.
The Emmy Computer Algebra System.
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.
List of resources & possible pathway for the Math of Machine Learning and AI.
☕ Symja - computer algebra language & symbolic math library. A collection of popular algorithms implemented in pure Java.
⌨ Importable dictionary for typing math symbols more easily on your Android phone by using keyboard shortcuts inspired by LaTeX
An experimental computer algebra system written in Go
Reverse Mode Automatic Differentiation for Julia
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