✨ Standard library for JavaScript and Node.js. ✨
Scientific computing with Perl
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
A java package for nd-array calculations
Computer Science PDF notes
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.
A flonum matrix module for CHICKEN Scheme.
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.
The code provides a collection of functions for matrix changes, including transposing, finding the rank, inverting, multiplying.
Complete numerical computing labs with pdf documents. You just need to change coding according to your question requirements.
Explore Python implementations of numerical methods for solving mathematical problems. Includes root-finding, integration, and more.
This repository contains Numerical Computing important concepts notes (leading to machine learning and approximately in every field of computer science) implemented in Python Notebooks.
Implementations and explorations of several pipelines and algorithms in Robotic Vision, as part of the Mobile Robotics (Monsoon 2020) class.
Project for the University of Bologna Numerical Computing course (a.y. 2021-22).
This repository contains data related to BS Computer Science
Exercises for the University of Bologna Numerical Computing course (a.y. 2021-22).
This repo contains work material for the course: CST82333 - Numerical Computing
image filters using convolution operations and mathematical kernels
Implementation of several numerical computing methods with Python /// by theMHD.
NumDynamics is an advanced random number generation system that combines C's performance with Python's analytical power. It generates, analyzes, and visualizes random numbers across various statistical distributions, offering a precise and efficient toolkit for random number analysis. 📊
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