Search Results for "data visualization, research" - Page 4
Sort By:
Showing 230 open source projects for "data visualization, research"
View related business solutions-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
Octave Forge
A collection of packages providing extra functionality for GNU Octave
...It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable. Refer to https://www.octave.org for more information. -
2
Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine... -
3
ProbabilisticCircuits.jl
Probabilistic Circuits from the Juice library
This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units).... -
4
Awesome Network Analysis
A curated list of awesome network analysis resources
awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
FastReport Open Source
Free Open Source Reporting tool for .NET
Free Open Source Reporting tool for .NET Core/.NET Framework that helps your application generate document-like reports. -
6
STLplus C++ library collection
C++ Library collection
Containers to extend STL: graph, tree, matrix, smart-pointer. Persistence (serialisation) of C++ data structures. Portability: subprocesses, TCP, file system. Reusable subsystems: library manager, message handler. Portable between OSs and compilers. Documentation is included in the download and is also available on the STLplus website http://stlplus.sourceforge.net. The headers are intended to be readable, so look at them too for usage information on each function and class. -
7
LinAsm
Collection of fast and optimized assembly libraries for x86-64 Linux
LinAsm is collection of very fast and SIMD optimized assembly written libraries for x86-64 Linux. It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract... -
8
ARC-AGI
The Abstraction and Reasoning Corpus
ARC-AGI is a benchmark dataset and experimental framework designed to evaluate and advance artificial general intelligence by testing systems on abstract reasoning tasks that require human-like problem-solving abilities. It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. The dataset is structured as grid-based puzzles, where each task requires... -
9
Tokenize.jl
Tokenization for Julia source code
Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
10
D3.js
A JavaScript library for visualizing data using web standards
D3.js (or D3 for Data-Driven Documents) is a JavaScript library that allows you to produce dynamic, interactive data visualizations in web browsers. With D3 you can bring data to life using SVG, Canvas and HTML. Powerful visualization and interaction techniques plus a data-driven approach to DOM manipulation means D3.js gives you greater design freedom and control over the final result. -
11
applied-ml
Papers & tech blogs by companies sharing their work on data science
The applied-ml repository is a rich, curated collection of papers, technical articles, and case-study blog posts about how machine learning (ML) and data-driven systems are applied in real production environments by major companies. Instead of focusing solely on theoretical ML research, this repo highlights industry-scale challenges: data collection, quality, infrastructure, feature stores, model serving, monitoring, scalability, and how ML is embedded in product workflows. It acts as a living library for practitioners who want to learn from real-world successes and failures — giving insight into how large organizations structure their data pipelines, how they manage ML lifecycle at scale, and what architectural or operational tradeoffs they made. ... -
12
AudioCraft
Audiocraft is a library for audio processing and generation
AudioCraft is a PyTorch library for text-to-audio and text-to-music generation, packaging research models and tooling for training and inference. It includes MusicGen for music generation conditioned on text (and optionally melody) and AudioGen for text-conditioned sound effects and environmental audio. Both models operate over discrete audio tokens produced by a neural codec (EnCodec), which acts like a tokenizer for waveforms and enables efficient sequence modeling. -
13
Glumpy
Python+Numpy+OpenGL, scalable and beautiful scientific visualization
...It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and creative exploration. -
14
prometheus-net
.NET library to instrument your code with Prometheus metrics
This is a .NET library for instrumenting your applications and exporting metrics to Prometheus. -
15
Bootstrap.jl
Statistical bootstrapping library for Julia
Bootstrapping is a widely applicable technique for statistical estimation. -
16
corlpack
Ada Library for heterogenous vectors
Corlpack consists of a library and tools aiming to simplify and accelerate programming of small, scientific, computational applications. One of the planned features is the loading and saving of a variety of research data into a single generic data structure, that is much like the named list from R, thus removing the need to learn many data access APIs. -
17
LMAX Disruptor
High performance inter-thread messaging library
...Clearly, in order to achieve this we needed to do something special to achieve very low-latency and high-throughput with our Java platform. Performance testing showed that using queues to pass data between stages of the system was introducing latency, so we focused on optimising this area. The Disruptor is the result of our research and testing. We found that cache misses at the CPU-level, and locks requiring kernel arbitration are both extremely costly, so we created a framework which has "mechanical sympathy" for the hardware it’s running on, and that’s lock-free. ... -
18
fastMRI
A large open dataset + tools to speed up MRI scans using ML
...The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. -
19
learn2learn
A PyTorch Library for Meta-learning Research
Learn2Learn is a PyTorch-based library focused on meta-learning and few-shot learning research. It provides reusable components and meta-learning algorithms, making it easier to build, train, and evaluate models that can quickly adapt to new tasks with minimal data. Learn2Learn is widely used in research for tasks such as few-shot classification, reinforcement learning, and optimization. -
20
DIG
A library for graph deep learning research
...It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
21
Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. -
22
libgwyfile
Read and write Gwyddion GWY files
Libgwyfile is a small, embeddable library for reading and writing of Gwyddion GWY files as foreign data. This means independently of Gwyddon and without adopting its data object model. -
23
AlgoNotes
Summary of articles from the official account of Qianmeng Study Notes
AlgoNotes is a curated technical knowledge repository focused on recommendation systems, search, advertising, and machine learning. It collects articles, engineering practices, research summaries, and interview materials in one organized index. Major sections cover ranking and conversion prediction, recall and matching, user profiles, and feature engineering. It also includes recommendation and search topics, computational advertising, big data, and graph algorithms. Additional material covers NLP, computer vision, technical discussions, and job interviews. ... -
24
Java Marine API
NMEA 0183 library for Java
Java Marine API is an NMEA 0183 library for Java. For furher info and latest source code, see project's Github pages. https://github.com/ktuukkan/marine-api/ -
25
ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. For someone trying to get up to speed...