Showing 14 open source projects for "matlab machine learning"

View related business solutions
  • Enterprise-grade ITSM, for every business Icon
    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
    Try it Free
  • Full-stack observability with actually useful AI | Grafana Cloud Icon
    Full-stack observability with actually useful AI | Grafana Cloud

    Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

    Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
    Create free account
  • 1
    PRML

    PRML

    PRML algorithms implemented in Python

    PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    The Algorithms Python

    The Algorithms Python

    All Algorithms implemented in Python

    ...Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    X's Recommendation Algorithm

    X's Recommendation Algorithm

    Source code for the X Recommendation Algorithm

    ...While certain components (such as safety layers, spam detection, or private data) are excluded, the release provides valuable insights into the design of real-world machine learning–driven ranking systems. The project is intended as a reference for researchers, developers, and the public to study, experiment with, and better understand the mechanisms behind social media content.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 4
    AStro inFER - a rule miner and executer
    Downloads: 0 This Week
    Last Update:
    See Project
  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build generative AI apps with Vertex AI. Switch between models without switching platforms.
    Start Free
  • 5
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no...
    Downloads: 4 This Week
    Last Update:
    See Project
  • 7
    GFPGAN

    GFPGAN

    GFPGAN aims at developing Practical Algorithms

    GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing...
    Downloads: 61 This Week
    Last Update:
    See Project
  • 8
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 9
    Active Learning

    Active Learning

    Framework and examples for active learning with machine learning model

    Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB 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.
    Start Free
  • 10

    MarketSim

    A python based auction market simulator for agricultural trade

    The market assumes an environment in which farmers sell their produce through brokers and traders locate produce to buy through brokers. The major aim of the simulator is to experiment with various reputation mechanisms to manage bottlenecks and to model various adversarial scenarios. The market is aimed to simulate agricultural trade in developing countries. It is written in python and mysql database on Linux.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 11

    PyVision Computer Vision Toolkit

    A Python computer vision library

    PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 12

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 13

    ktree

    clustering, machine learning, algorithms

    This project has moved to github at http://lmwtree.devries.ninja.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 14
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB