Open source

Si segnalano alcuni programmi Open Source.
Inviaci una tua segnalazione.

  • Accord.NET
    Accord.NET Framework è un framework di machine learning .NET combinato con librerie di elaborazione di immagini e audio completamente scritte in C#. Si tratta di un framework completo per la creazione di applicazioni di computer vision, computer auditing, elaborazione del segnale e statistiche di livello produttivo anche per uso commerciale.
  • Apache Mahout(TM)
    Is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end, or can be extended to other distributed backends. Mathematically Expressive Scala DSL Support for Multiple Distributed Backends (including Apache Spark) Modular Native Solvers for CPU/GPU/CUDA Acceleration
  • Apache SystemDS
    Machine learning using big data. It can be run on top of Apache Spark or standalone, where it automatically scales your data, line by line, determining whether your code should be run on the driver or an Apache Spark cluster. SystemDS include additional deep learning with GPU capabilities such as importing and running neural network architectures and pre-trained models for training.
  • Apple Core ML 
    Integrate machine learning models into your app.
  • Caffe
    Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license.
  • Cloud AutoML
    Addestra modelli personalizzati di machine learning di alta qualità con un impegno minimo, senza necessità di disporre di competenze approfondite nell’ambito del machine learning.
  • Colaboratory
    “Colab” ti permette di scrivere ed eseguire codice Python nel tuo browser con i seguenti vantaggi: Nessuna configurazione necessaria; Accesso gratuito alle GPU; Condivisione semplificata. Che tu sia studente, data scientist o ricercatore AI, Colab può semplificarti il lavoro.
  • Crowdsource
    Verifica le didascalie delle immagini. La verifica delle didascalie generate automaticamente consente di rendere le immagini più accessibili alle persone con disabilità visive e cognitive.
  • Datasets
    In order to contribute to the broader research community, Google periodically releases data of interest to researchers in a wide range of computer science disciplines.
  • Datasets Search
  • Deeplearning4J
    The KNIME Deeplearning4J Integration allows to use deep neural networks in KNIME. The extension consists of a set of new nodes which allow to modularly assemble a deep neural network architecture, train the network on data, and use the trained network for predictions. Furthermore, it is possible to write/read a trained or untrained network to/from disk which allows to share and reuse the created networks.
  • Fairness-indicators
    Fairness Indicators is designed to support teams in evaluating, improving, and comparing models for fairness concerns in partnership with the broader Tensorflow toolkit. The tool is currently actively used internally by many of our products. We would love to partner with you to understand where Fairness Indicators is most useful, and where added functionality would be valuable. Please reach out at
  • IBM Watson
    Powered by the latest innovations in machine learning, Watson lets you learn more with fewer data. You can integrate AI into your most important business processes, informed by IBM’s rich industry expertise. You can build models from scratch, or leverage our APIs and pre-trained business solutions. No matter how you use Watson, your data and insights belong to you − and only you.
    Learn from ML experts at Google. Whether you’re just learning to code or you’re a seasoned machine learning practitioner, you’ll find information and exercises to help you develop your skills and advance your projects.
  • Open Source Live
    Google open source experts host monthly events focused on different open source technologies and areas of expertise. Each event includes multiple sessions and a live Q&A.
  • Prodotti di AI e machine learning
    Prodotti e servizi innovativi di machine learning su una piattaforma affidabile.
  • Keras 
    Deep learning for humans. Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides.
  • Machine learning for mobile developers
    ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package. Make your iOS and Android apps more engaging, personalized, and helpful with solutions that are optimized to run on device.
  • Mycroft
    AI For Everyone. Is the world’s leading open source voice assistant. It is private by default and completely customizable. Our software runs on many platforms—on desktop, our reference hardware, a Raspberry Pi, or your own custom hardware. The Mycroft open source voice stack can be freely remixed, extended, and deployed anywhere. Mycroft may be used in anything from a science project to a global enterprise environment.
  • Open Cog
    Building better minds together… No challenge today is more important than creating beneficial artificial general intelligence (AGI), with broad capabilities at the human level and ultimately beyond. OpenCog is an open-source software initiative aimed at directly confronting that challenge.
  • OpenCV 
    An Open Source Machine Learning and Computer Vision Software
  • OpenNN
    Build the most powerful models with C++ OpenNN is an open-source neural networks library for machine learning. It solves many real-world applications in energy, marketing, health, and more
  • Neuroph
    Is a maintainance release and comes with minor API improvements, cleanup of unstable features and bugfixes. From this version Neuroph is also available on Maven Central repository.
  • PyTorch 
    FROM RESEARCH TO PRODUCTION An open source machine learning framework that accelerates the path from research prototyping to production deployment.
  • Scikit learn 
    Simple and efficient tools for predictive data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable – BSD license
  • SimpleCV
    SimpleCV is an open source framework for building computer vision applications. With it, you get access to several high-powered computer vision libraries such as OpenCV – without having to first learn about bit depths, file formats, color spaces, buffer management, eigenvalues, or matrix versus bitmap storage. This is computer vision made easy.
  • TensorFlow
    Una piattaforma di machine learning open source end-to-end. Per JavaScriptPer dispositivi mobili e IoTPer la produzione. La libreria open source principale per aiutarti a sviluppare e addestrare modelli ML. Inizia rapidamente eseguendo i taccuini Colab direttamente nel tuo browser.
  • Tesseract OCR
    An optical character recognition (OCR) engine. Tesseract is an OCR engine with support for unicode and the ability to recognize more than 100 languages out of the box. It can be trained to recognize other languages. How Google uses Tesseract OCR. Tesseract is used for text detection on mobile devices, in video, and in Gmail image spam detection.
  • Torch
    Is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.