numerical-computing
There are 4 repositories under numerical-computing topic.
- Language:JavaScript 5464
PDLPorters / pdl
Scientific computing with Perl
Language:Perl 98farukalpay / FABE
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.
Language:C 53SciScala / NDScala
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
Language:Scala 47ishmahafeez / Computer-Science-Notes
Computer Science PDF notes
rohanmistry231 / Numpy-Interview-Preparation
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.
Language:Python 14chenmingxiang110 / J4darrays
A java package for nd-array calculations
Language:Java 13shahzaibk23 / Numerical-Computing-Python
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.
Language:Jupyter Notebook 10muditbhargava66 / FFT-implementation-in-C
The repository provides code, build instructions, and usage guidelines for each FFT implementation.
Language:C 6- Language:C 5
AayushKotwani3 / Numpy-masterclass
Comprehensive hands-on notes, examples, and exercises to master NumPy from basics to advanced.
Language:Jupyter Notebook 4- matricoLanguage:Scheme 3
- Language:C++ 3
HolubievIllya / Matrix-Operations-Python
The code provides a collection of functions for matrix changes, including transposing, finding the rank, inverting, multiplying.
Language:Python 3shafaq-aslam / numpy-lab
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.
Language:Jupyter Notebook 3arbitrary-number / arbitrary-number
Arbitrary Numbers
Language:Python 2labex-labs / numpy-practice-challenges
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.
- NumericalAnalysis
muhammad-umaair / NumericalAnalysis
Complete numerical computing labs with pdf documents. You just need to change coding according to your question requirements.
Language:Jupyter Notebook 2 NechbaMohammed / OptiNumPy
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.
Language:Python 2Sourabh-Kumar04 / Numpy-Basic
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.
Language:Jupyter Notebook 2Abdirashid-dv / Numerical-Methods-Using-Python
Explore Python implementations of numerical methods for solving mathematical problems. Includes root-finding, integration, and more.
Language:Python 1Abhrankan-Chakrabarti / sqrt
A high-precision square root calculator written in Rust using the Malachite library. Supports both interactive and command-line modes, allowing users to compute the square root of any positive integer to an arbitrary number of decimal digits with fixed-point accuracy.
Language:Rust 1AitzazTahirCh / Numerical-Computing
This repository contains Numerical Computing important concepts notes (leading to machine learning and approximately in every field of computer science) implemented in Python Notebooks.
Language:HTML 1NumPy is an extension library for Python language, supporting operations of a large number of high-dimensional arrays and matrices. In addition, it also provides a large number of mathematical function libraries for array operations. Machine learning involves a lot of transformations and operations on arrays, which makes NumPy one of the essenti...
NeuralAditya / Polynomial_Regression_C
A high-performance polynomial regression implementation in pure C with gradient descent optimization and visualization support.
Language:C 1abbaskhan0345 / numpy-learning
NumPy Essentials in Python – A collection of examples and mini-projects demonstrating array manipulation, mathematical operations, broadcasting, and performance optimization using NumPy. This repo showcases key concepts for scientific computing and data analysis workflows.
Language:Jupyter NotebookAS-0167 / zero-hunter
Zero Hunter - A comprehensive C-based root-finding toolkit implementing five numerical methods with modular design, multiple stopping criteria, and extensive testing capabilities for solving nonlinear equations.
Language:CAyikoandrew / odin-ML
Exploring Machine Learning at a low level. Implementing algorithms from scratch in Odin, one Sunday at a time.
Language:Odinharinandanmv / numpy-practice
A collection of beginner-friendly NumPy tasks designed to explore fundamental array operations in Python. Covers array creation, reshaping, slicing, mathematical operations, identity matrices, random data generation, and more — perfect for hands-on practice and foundational learning in scientific computing with NumPy.
Language:Jupyter Notebookkandarpa02 / hiphop
TensorFlow with rhythm — simple, flexible neural networks without the Keras overhead.
Language:PythonThis comprehensive course covers the fundamental concepts and practical techniques of NumPy, the essential library for numerical computing in Python. Learn to create, manipulate, and analyze arrays efficiently.
Mahsa-Goudarzi / scientific-computing-tools-course
The exercises for the course "Scientific computing tools" - Autumn 2024
Language:Jupyter Notebooknabilshadman / learning-jax-numerical-computing-machine-learning
Exercise files of the Learning JAX course (on LinkedIn Learning)
Language:Jupyter Notebookrtgrt5645 / numpy-lab
🧮 Explore, manipulate, and visualize data with NumPy to enhance your Python skills in scientific computing and data analysis.
Language:Jupyter NotebookSatvikPraveen / OctaveMasterPro
Advanced numerical computing framework with GNU Octave featuring parallel processing, optimization algorithms, statistical analysis, and comprehensive data science applications. Includes Dockerized Jupyter environment, financial modeling, signal/image processing pipelines, industrial analytics, and real-world demonstrations.
algorithm-implementationcomputational-mathematicsdata-analyticsdata-sciencedocker-environmentfinancial-modelinggnu-octavehigh-performance-computingimage-processingjupyter-notebooklinear-algebramatrix-computationsnumerical-computingoptimization-algorithmsparallel-processingperformance-optimizationpredictive-maintenancescientific-computingsignal-processingstatistical-analysisLanguage:MATLABSidra-009 / Numpy-Practice
Practice codes and examples of NumPy basics including array creation, indexing, slicing, broadcasting, random functions, and visualization with Matplotlib.
Language:Jupyter Notebook
