✨ The fundamental numerical library for JavaScript and TypeScript. ✨

Scientific computing with Perl

High-accuracy SIMD sin/cos/sincos library in C with AVX2, AVX-512, and NEON support. Full-range reduction. Fast at scale. Portable by design.

N-dimensional / multi-dimensional arrays (tensors) in Scala 3. Think NumPy ndarray / PyTorch Tensor but type-safe over shapes, array/axis labels & numeric data types

Computer Science PDF notes

A focused resource for mastering NumPy, featuring practice problems, code examples, and interview-oriented numerical computing techniques in Python. Covers array operations, linear algebra, and performance optimization for data science interviews.

A java package for nd-array calculations

Python implementation of Methods and Algorithm or Numerical Computing Course. You just have to Enter the input values from the question and All the iterations will be generated automatically.

The repository provides code, build instructions, and usage guidelines for each FFT implementation.

a basic numpy-like library in c with broadcasting :)

Comprehensive hands-on notes, examples, and exercises to master NumPy from basics to advanced.

A flonum matrix module for CHICKEN Scheme.

The code provides a collection of functions for matrix changes, including transposing, finding the rank, inverting, multiplying.

This repository contains the source code and documentation for the OptiNumPy library, a numerical analysis optimization package written in Python. The library provides various numerical optimization algorithms for solving optimization problems.

A structured collection of Jupyter notebooks exploring NumPy from the ground up; covering array creation, manipulation, broadcasting, indexing, and data visualization for scientific computing and data analysis.

Complete numerical computing labs with pdf documents. You just need to change coding according to your question requirements.

This course contains lots of challenges for NumPy, each challenge is a small NumPy project with detailed instructions and solutions. You can practice your NumPy skills by solving these challenges, improve your problem-solving skills, and learn how to write clean and efficient code.

Numpy-Basic is a structured learning repo covering NumPy from basics to advanced. It includes arrays, indexing, reshaping, filtering, vector ops, angle functions, stats, and .npy file handling. Each concept is explained with code, examples, and Matplotlib visualizations in both light and dark modes. Ideal for students and data learners.

Arbitrary Numbers