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A guide that introduces data processing and cleaning in JavaScript, teaching how to load, modify and transform data using JavaScript libraries. It covers tasks geared around preparing data for further analysis and visualization, demonstrated with core JavaScript API, d3.js and lodash. It assumes some basic knowledge of JavaScript.
Pipcook is a JavaScript application framework for machine learning and its engineering, aimed at Web developers. It provides subprojects including a machine learning pipeline framework, management tools and a JavaScript runtime for machine learning. A Pipcook Pipeline composes scripts and outputs an NPM package containing the trained model and JavaScript functions. The documentation describes a workflow of install, train, test and deploy using the Pipcook command-line tool.
Twitter Text Java is the Java implementation of the twitter-text parsing library. It provides methods and classes to parse Tweets, calculate length, check validity, and parse @mentions, #hashtags, and URLs. Artifacts are published to Maven Central.
Brain.js is a GitHub-hosted JavaScript library for building and running neural networks. It provides GPU-accelerated neural network functionality compatible with both web browsers and Node.js environments, allowing users to implement machine learning models using JavaScript across different runtime platforms.
Stanford CoreNLP is a set of natural language analysis tools that take raw text and produce base word forms, parts of speech, named entities, normalized dates and numeric quantities, sentence structure and sentiment. It is an integrated Java framework licensed under the GNU General Public License v3 or later, with a 260 MB download requiring Java 1.8+.
Deeplearning4j is an open-source suite of tools for deploying and training deep learning models using the Java Virtual Machine (JVM). It supports model import from Keras, TensorFlow, and ONNX/PyTorch, includes a modular C++ math library with a corresponding Java library built on top, and offers SameDiff, a library for deep learning operations similar to PyTorch and TensorFlow.
A Java scientific and numerical library written by Michael Thomas Flanagan to support his research and undergraduate programming courses. It is distributed as the flanagan.jar package and includes general classes, example programs and arbitrary precision methods. The author has retired and states it will be updated less frequently. Commercial use, public listing of source codes and redistribution are not permitted.
A reference page in the Clojure documentation covering Java interop, including class access, member access, the dot special form, implementing interfaces and extending classes, arrays, vararg methods and type hints.
A book titled JavaScript for Data Science by Maya Gans, Toby Hodges, and Greg Wilson, version 4.0, dated January 2020. It covers topics such as callbacks, promises, objects, classes, HTML, CSS, React, data services, testing, data visualization, and a three-tier web application, with an even mix of browser and server programming. It is intended for scientists and engineers.
A reference page for ClojureScript's JavaScript API covering the stable, publicly consumable indexOf and lastIndexOf functions. These get the index of a value in a sequential collection, or -1 if not found, with an optional starting index for the search.
KotlinDL is a high-level deep learning API written in Kotlin and inspired by Keras. It uses TensorFlow Java API and ONNX Runtime API for Java, and offers APIs for training models from scratch, importing Keras and ONNX models for inference, and transfer learning.
An R package that creates interactive Leaflet maps using the Leaflet JavaScript library and htmlwidgets. Maps can be used from the R console, RStudio, Shiny applications and R Markdown documents. It is linked to the open-source Leaflet JavaScript library for interactive maps.
Neuroph is a lightweight, open source Java neural network framework released under the Apache 2.0 license. It provides a Java library and a GUI editor, Neuroph Studio, based on the NetBeans Platform, for creating, training and saving neural networks. It supports architectures including Perceptron, Multi Layer Perceptron, Hopfield, Kohonen and RBF networks, and both supervised and unsupervised learning rules.
Sigma.js is a WebGL-powered JavaScript library for interactive graph visualization, built on graphology. It provides GPU-accelerated rendering, built-in pan, zoom, hover and multi-touch interactions, and works with React, Angular, Vue or vanilla JavaScript. Layouts, metrics and community detection come via graphology's standard library.
Simple Statistics is a JavaScript implementation of descriptive, regression, and inference statistics. It is written in literate JavaScript with no dependencies and is designed to work in all modern browsers and in Node.js. The repository is published under an ISC license.
ZingChart is a dependency-free pure JavaScript charting library for data visualization. It includes over 50 built-in chart types and modules, uses simple JSON configuration, and offers integrations with popular JavaScript frameworks including React, Angular, and Vue.
Aerosolve is a machine learning package built on the JVM. It provides features such as geo-based features, controllable quantization and feature interaction, and a feature transform language that gives developers control over features. General additive models are used. Scala handles feature training, with a lightweight Java API for run time inference.
Agentset.ai is an open-source platform for building AI chat and search applications. It provides production-grade retrieval-augmented generation (RAG) capabilities without requiring specialized RAG expertise, and includes features such as multimodal support, automatic source citations, metadata filtering, support for over 22 file formats, and JavaScript and Python SDKs.
Aider LLM Leaderboards presents quantitative benchmarks of LLM code editing skill. The polyglot benchmark tests LLMs on 225 Exercism coding exercises in C++, Go, Java, JavaScript, Python and Rust, and benchmarks evaluate an LLM's ability to follow instructions and edit code without human intervention.
amCharts is a TypeScript library for JavaScript charts, offering 60+ chart types plus maps, stock charts, and Gantt charts. The site states the library is free to use and React-ready. Documentation lists React, Angular, Vue.js, Next.js, and other integrations.
A Java Toolbox for Scalable Probabilistic Machine Learning.
AnyChart is a JavaScript charting library with an API and documentation. It offers a large number of chart types, and the site lists related products for stock charts, HTML5 maps and Gantt charts. Version 9.0.0 added chart types including arc diagram, dependency wheel, org chart, stream graph, waffle chart, lollipop and dumbbell. The library is described as working with any development stack.
Bowtie is a library for writing dashboards in Python. It wraps the code needed for interactive data exploration and visualization, so users can build functionality without knowing web frameworks or JavaScript. It can be installed with conda or pip, and Docker images are provided.
Catniff is a small deep learning framework for JavaScript built to be Torch-like and inspired by Tinygrad APIs. It is under development, and its APIs can be unstable and backwards-incompatible. It provides tensors, autograd and optimizers, and is installed through npm.
