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Published directory entries matching your search.
This page is the Simple Widget Introduction of the Jupyter Widgets documentation. It describes widgets as eventful Python objects with a browser representation, used to build interactive GUIs for notebooks and synchronize information between Python and JavaScript. It covers display, views, closing widgets, and properties.
A Clojure wrapper for deeplearning4j with added syntactic sugar, aiming to provide a declarative API for machine learning on the JVM. It translates Clojure keywords into Java method calls, making many deeplearning4j configuration options accessible. The project is a work in progress, and configurations have been tested on basic feedforward nets, RNNs and CNNs.
A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
JavaScript implementation of the k nearest neighbors algorithm for supervised learning.
KNIME Analytics Platform is free and open source data analytics software with a visual workflow builder for creating data science solutions. The page lists access, blending and transformation of data from any source, visualization and analysis, and saving, sharing and reuse of workflows. It also describes integrating scripting in Python, R and JavaScript and deploying solutions in the enterprise.
Just a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.
Knwl.js is a JavaScript library that parses text for dates, times, phone numbers, emails, places and more. Parser plugins supply parsing abilities, and the library runs in the browser or on the server with Node.js.
LDA is a JavaScript library for node.js that performs Latent Dirichlet allocation topic modeling, extracting topics and related keywords from a collection of documents. It returns an array of topics, each with an array of terms and probabilities, and uses English stop-words by default.
Supports teaching, studying or skills practice with AI-guided learning tools.
m2cgen is a tool that transforms trained machine learning models into native code across a wide range of programming languages including Java, C, Python, Go, JavaScript, C#, R, PHP, Dart, Haskell, Ruby, F#, and Rust, with zero dependencies. Its codebase is hosted in the BayesWitnesses GitHub repository, which includes navigation for installation, development guidance, supported languages, and supported model types.
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. It includes tools for converting text to features, classifiers such as Naïve Bayes, Maximum Entropy and Decision Trees, sequence tagging with Hidden Markov Models and Conditional Random Fields, and sampling-based topic model implementations.
Mengram is an open-source project that provides human-like memory capabilities for AI agents. It supports semantic, episodic, and procedural memory types, with experience-driven procedures designed to learn from failures. The project offers a free API, Python and JavaScript SDKs, and integrations with LangChain, CrewAI, and OpenClaw.
MITIE is a set of tools for information extraction built on dlib. It provides named entity extraction and binary relation detection, along with tools for training custom extractors and relation detectors. Pre-trained models support English, Spanish and German. The core is written in C++, with bindings for Python, R, Java, C and MATLAB.
ml.js is an open-source machine learning toolset implemented in JavaScript, hosted in the mljs/ml GitHub repository. It provides libraries for both supervised and unsupervised machine learning tasks, alongside usage resources and standalone example code for users.
ml5.js is a JavaScript library providing access to machine learning algorithms and models in the browser, building on TensorFlow.js. It aims to make machine learning approachable for artists, creative coders and students, and is supported by code examples, tutorials and sample data sets. The project is described as currently in development.
Neanderthal is a Clojure library for fast native matrix and linear algebra, built with native BLAS and LAPACK for number crunching and wrapped in a small Clojure layer. It offers pluggable engine implementations, including a pure Java engine, plus primitive versions of map and reduce.
Compromise is a JavaScript natural-language processing library that turns text into data, offering tokenization of words, sentences and punctuation along with part-of-speech tagging, matching, and transformations such as verb conjugation and number handling. It runs on the client side, is about 250kb minified, and includes plugins, with multilingual support listed for French, German, Italian and Spanish.
nlp.js is a JavaScript library for building chatbots and bots, developed by AXA Group. It includes features such as entity extraction, sentiment analysis, and automatic language identification. The library is open-source and hosted on GitHub.
Node-SVM is a GitHub repository that provides support vector machine (SVM) implementations for Node.js. The project enables developers to use SVM algorithms within JavaScript applications. It includes installation instructions, a quick start guide, and an API reference. The repository is open source and contributed to by the community.
NSFWJS is a simple JavaScript library that identifies unseemly images directly in a user's web browser. The library is noted as reasonably accurate, with ongoing work to improve its performance.
OpenCV is an open source computer vision library that contains over 2500 algorithms and supports model execution for machine learning and artificial intelligence. It was designed to be cross-platform, written in C with C++ and wrappers for Python and Java, and runs on desktop and mobile systems. A GPU module implemented with CUDA provides acceleration for part of the library.
Optunity is a Python library containing various optimizers for hyperparameter tuning. It provides several approaches to solving tuning problems, including cross-validation facilities and score functions. The documentation states it is supported in R, MATLAB, GNU Octave and Java through Jython, and is free software under a BSD-style license.
Pavlov.js is a reinforcement learning library that uses Markov Decision Processes. It is written in C++ and compiled to JavaScript. The package is installed through npm. Users define transitions and rewards, then call learn to derive a policy and query actions for states.
Rapaio is a statistics, data mining, and machine learning toolbox written in Java. It includes distributions, hypothesis testing, Naive Bayes, logistic regression, decision trees, random forests, boosting, SVM, PCA, and KMeans.
