There are 25 repositories under calculus topic.
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 Android C# .NET/MONO (.NET Framework, .NET Core, .NET Standard, .NET PCL, Xamarin.Android, Xamarin.iOS) CLS Library - a super easy, rich and flexible mathematical expression parser (expression evaluator, expression provided as plain text / strings) for JAVA and C#. Main features: rich built-in library of operators, constants, math functions, user defined: arguments, functions, recursive functions and general recursion (direct / indirect). Additionally parser provides grammar and internal syntax checking.
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.
Power calculator for Android. Solve some problem algebra and calculus.
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
➗ A really micro micro-service for advanced math.
List of resources & possible pathway for the Math of Machine Learning and AI.
An experimental computer algebra system written in Go
The Emmy Computer Algebra System.
:coffee: 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
Reverse Mode Automatic Differentiation for Julia
Complete path for a beginner to become a Machine Learning Scientist!
😎 📜 Collection of the most awesome Maths learning resources in the form of notes, videos and cheatsheets.
Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
Computator.NET is a special kind of numerical software that is fast and easy to use but not worse than others feature-wise. It's features include: - Real and complex functions charts - Real and complex calculator - Real functions numerical calculations including different methods - Over 107 Elementary functions - Over 141 Special functions - Over 21 Matrix functions and operations - Scripting language with power to easy computations including matrices - You can declare your own custom functions with scripting language
Scalable symbolic-numeric set computations in Julia
VIP cheatsheets for Stanford's CME 102 Ordinary Differential Equations for Engineers
moved to https://github.com/desicochrane/datasci
Planning for an entire maths LaTeX book
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.
A collection of Mathematics + CS + what have you related books collected over the years for school 🎓 and personal reading 📚.
As described in Advances of Machine Learning by Marcos Prado.
Solutions to In-Class questions, Problem Sets and Exams of MIT Mathematics for Computer Science 2015 (same as 2019 Open Learning Library)
This repo contains some code which can graph equations in a UIView.
Open-source project hosted at https://makeuseofdata.com to crowdsource a robust collection of notes related to data science (math, visualization, modeling, etc)