Computing Libraries

51 Components & Libraries

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Computing Libraries

Data Apps & Dashboards for Python. No JavaScript Required.

With Dash Open Source, Dash apps run on your local laptop or workstation, but cannot be easily accessed by others in your organization. Scale up with Dash Enterprise when your Dash app is ready for d…

SciPy library main repository

SciPy (pronounced "Sigh Pie") is an open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, …

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Install CatBoost by following the guide for the Next you may want to investigate: If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domain…

:rocket: Build and manage real-life ML, AI, and data science projects with ease!

There are several ways to get in touch with us:

Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.

This library is the core component of Qiskit, which contains the building blocks for creating and working with quantum circuits, quantum operators, and primitive functions (sampler and estimator). It…

Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and algorithms.

This framework allows for building, transforming, and visualizing quantum circuits. It also contains a compiler that supports different quantum computers and a common interface for running programs …

C++ implementation of the Python Numpy library

The random module provides simple ways to create random arrays.

A list of resources in different fields of Computer Science

Evolutionary algorithm toolbox and framework with high performance for Python

The Genetic and Evolutionary Algorithm Toolbox for Python with high performance. The features of Geatpy: Capability of solving single-objective, multi-objectives, many-objectives and combinatorial op…

Medical imaging toolkit for deep learning

If you like this repository, please click on Star! If you use this package for your research, please cite our paper: BibTeX entry: This project is supported by the following institutions:

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.

Below you can find a GPU multiplication example using the C++ and Python Kompute interfaces. You are able to try out the interactive Colab Notebooks which allow you to use a free GPU. The available e…

Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.

The Insight Toolkit (ITK) is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration. Segmentation is the process of identifying and class…

Multi-platform, free open source software for visualization and image computing.

Slicer, or 3D Slicer, is a free, open source software package for visualization and image analysis. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and …

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

Experiments are produced on MNIST, Fashion MNIST and CIFAR10 (both IID and non-IID). In case of non-IID, the data amongst the users can be split equally or unequally. Since the purpose of these exper…

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

Adaptive is an open-source Python library that streamlines adaptive parallel function evaluations. Rather than calculating all points on a dense grid, it intelligently selects the "best" points in th…

MapReduce, Spark, Java, and Scala for Data Algorithms Book

The book's codebase can also be downloaded from the git repository at: Thank you!

Pythonic tool for running machine-learning/high performance/quantum-computing workflows in heterogeneous environments.

Covalent is a Python library for AI/ML engineers, developers, and researchers. It provides a straightforward approach to running compute jobs, like LLMs, generative AI, and scientific research, on v…

An elegant Python interface for visualization on the web platform to interactively generate insights into multidimensional images, point sets, and geometry.

ITKWidgets is an elegant Python interface for visualization on the web platform to interactively generate insights into multidimensional images, point sets, and geometry. To install for all environme…

Python Computer Vision & Video Analytics Framework With Batteries Included

⭐ Star us on GitHub — it motivates us a lot and helps the project become more visible to developers. Savant is an open-source, high-level framework for building real-time, streaming, highly efficient…

Fast EMD for Python: a wrapper for Pele and Werman's C++ implementation of the Earth Mover's Distance metric

You can also get the associated minimum-cost flow: You can also calculate the EMD directly from two arrays of observations:

Tool-box for efficient build and debug in Python. Especially for Scientific Computing and Computer Vision.

So, all Tools are divided into 2 parts by wether the tool is general used: There are 3 methods to run or view this Notebook file Just view the Tutorial Notebook. Examples are divided into 2 parts too…

A framework for high-performance medical image processing, neural network inference and visualization

FAST is an open-source framework with the main goal of making it easier to do high-performance processing, neural network inference, and visualization of medical images utilizing multi-core CPUs and …

🗣️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts).

First, clone the repository and submodules: Now you have all the dependencies necessary to follow along with the chapters in the book. You don’t need to worry about any other installations. Any feedb…

Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:

If you use pip and don't have JAX installed already, you will also need to do: Running this script on 4 processes gives:

Fundamentals of Spark with Python (using PySpark), code examples

But, PySpark+Jupyter combo needs a little bit more love :-) Resilient Distributed Datasets (RDD) is a fundamental data structure of Spark. It is an immutable distributed collection of objects. Each d…

Neural networks toolbox focused on medical image analysis

A neural networks toolbox with a focus on medical image analysis in tensorflow/keras for now. If you use this code, please cite: If you are using any of the sparse/imputation functions, please cite:

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