Search Results for "artificial intelligence java source code" - Page 2

Showing 486 open source projects for "artificial intelligence java source code"

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  • 1
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology...
    Downloads: 1 This Week
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  • 2
    Gen.jl

    Gen.jl

    A general-purpose probabilistic programming system

    An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language...
    Downloads: 1 This Week
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  • 3
    Matter AI

    Matter AI

    Matter AI is open-source AI Code Reviewer Agent

    Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries.
    Downloads: 1 This Week
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  • 4
    txtai

    txtai

    Build AI-powered semantic search applications

    txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid...
    Downloads: 1 This Week
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  • 5
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing...
    Downloads: 1 This Week
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  • 6
    Avalanche

    Avalanche

    End-to-End Library for Continual Learning based on PyTorch

    Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL...
    Downloads: 1 This Week
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  • 7
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    ... code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.
    Downloads: 1 This Week
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  • 8
    GPT All Star

    GPT All Star

    AI-powered code generation tool for scratch development of web apps

    AI-powered code generation tool for scratch development of web applications with a team collaboration of autonomous AI agents. This is a research project, and its primary value is to explore the possibility of autonomous AI agents.
    Downloads: 0 This Week
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  • 9
    DotVVM

    DotVVM

    Open source MVVM framework for Web Apps

    DotVVM is an open-source framework for ASP.NET. It lets you create web apps using the MVVM pattern, with just C# and HTML. DotVVM can be used to build new ASP.NET Core web apps, or to modernize legacy ASP.NET apps and migrate them to .NET 5. Save your time with GridView, FileUpload and other components shipped with the framework. Don't spend the time building an API. Just load data from the database and use data-binding to display them. DotVVM needs less than 100 kB of JavaScript code. It's...
    Downloads: 1 This Week
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  • 10
    Bot Framework Web Chat

    Bot Framework Web Chat

    A highly-customizable web-based client for Azure Bot Services

    This repository contains code for the Bot Framework Web Chat component. The Bot Framework Web Chat component is a highly-customizable web-based client for the Bot Framework V4 SDK. The Bot Framework SDK v4 enables developers to model conversation and build sophisticated bot applications. This repo is part of the Microsoft Bot Framework, a comprehensive framework for building enterprise-grade conversational AI experiences. Create a bot with the ability to speak, listen, understand, and learn...
    Downloads: 1 This Week
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  • 11
    AIaC

    AIaC

    Artificial Intelligence Infrastructure-as-Code Generator

    aiac is a command line tool to generate IaC (Infrastructure as Code) templates, configurations, utilities, queries and more via OpenAI's API. The CLI allows you to ask the model to generate templates for different scenarios (e.g. "get terraform for AWS EC2"). It will make the request, and store the resulting code to a file, or simply print it to standard output. By default, aiac uses the same model used by ChatGPT, but allows using different models.
    Downloads: 0 This Week
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  • 12
    BotSharp

    BotSharp

    AI Multi-Agent Framework in .NET

    ... technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. It's written in C# running on .Net Core that is full cross-platform framework. C# is a enterprise-grade programming language which is widely used to code business logic in information management-related system.
    Downloads: 0 This Week
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  • 13
    Tribuo

    Tribuo

    Tribuo - A Java machine learning library

    Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts...
    Downloads: 0 This Week
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  • 14
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement...
    Downloads: 0 This Week
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  • 15
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    ... they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. Aim is an open-source experiment tracker that logs your training runs, and enables a beautiful UI to compare them.
    Downloads: 0 This Week
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  • 16
    Reviewpad

    Reviewpad

    Next generation pull requests and issues

    Reviewpad is a service to automate pull requests and issues workflows. The workflows are specified in a YML-based configuration language described in the official documentation. In Reviewpad, you can automate actions over the pull requests and issues. With technological progress depending on the human ability to create and modify software systems, Reviewpad was founded to allow developers to safely contribute to any codebase as fast as possible. Developers deserve a better experience and...
    Downloads: 0 This Week
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  • 17
    Mentat

    Mentat

    Mentat - The AI Coding Assistant

    Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them...
    Downloads: 0 This Week
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  • 18
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    ... continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization.
    Downloads: 0 This Week
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  • 19
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    ... ship with Sonnet, making it quite powerful and yet simple at the same time. Users are also encouraged to build their own modules. Sonnet is designed to be extremely unopinionated about your use of modules. It is simple to understand, and offers clear and focused code.
    Downloads: 0 This Week
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  • 20
    MIVisionX

    MIVisionX

    Set of comprehensive computer vision & machine intelligence libraries

    MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference...
    Downloads: 0 This Week
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  • 21
    Void Editor

    Void Editor

    Open source AI IDE and Cursor alternative

    Void is an open-source, AI-powered code editor built as a fork of Visual Studio Code. Designed as a fully transparent and privacy-focused alternative to Cursor or GitHub Copilot, it lets you use AI models locally or via APIs (OpenAI, Claude, Gemini, Ollama, etc.)—without routing data through proprietary servers. Developed by YC-backed startup Glass Devtools, it supports traditional coding features inherited from VS Code, enhanced with in-editor LLM capabilities—autocomplete, inline quick edits...
    Downloads: 0 This Week
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  • 22
    CodiumAI PR-Agent

    CodiumAI PR-Agent

    AI-Powered tool for automated pull request analysis

    CodiumAI PR-Agent is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of commands. See the Usage Guide for instructions how to run the different tools from CLI, online usage, Or by automatically triggering them when a new PR is opened. You can try GPT-4 powered PR-Agent, on your public GitHub repository, instantly. Just mention @CodiumAI-Agent and add the desired command...
    Downloads: 0 This Week
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  • 23
    spaGO

    spaGO

    Self-contained Machine Learning and Natural Language Processing lib

    ... to ensure that additional dependencies are downloaded only when specific features (e.g. persistent embeddings) are used. A good place to start is by looking at the implementation of built-in neural models, such as the LSTM. Except for a few linear algebra operations written in assembly for optimal performance (a bit of copying from Gonum), it's straightforward Go code, so you don't have to worry.
    Downloads: 0 This Week
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  • 24
    Lightly

    Lightly

    A python library for self-supervised learning on images

    A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training...
    Downloads: 0 This Week
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  • 25
    satellite-image-deep-learning

    satellite-image-deep-learning

    Resources for deep learning with satellite & aerial imagery

    This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful please...
    Downloads: 0 This Week
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