Showing 86 open source projects for "machine learning python"

View related business solutions
  • Cut Data Warehouse Costs by 54% Icon
    Cut Data Warehouse Costs by 54%

    Easily migrate from Snowflake, Redshift, or Databricks with free tools.

    BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
    Start Free
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
    Start Free
  • 1
    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust.
    Downloads: 3 This Week
    Last Update:
    See Project
  • 2
    LearnOpenCV

    LearnOpenCV

    C++ and Python Examples

    LearnOpenCV is a large educational repository that provides practical computer vision and deep learning examples in both Python and C++. The project accompanies the LearnOpenCV blog and contains hundreds of hands-on tutorials covering topics such as object detection, image processing, pose estimation, and neural networks. It is structured as a learning resource where each directory corresponds to a specific article or technical walkthrough.
    Downloads: 5 This Week
    Last Update:
    See Project
  • 3
    libvips

    libvips

    A fast image processing library with low memory needs

    libvips is a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good...
    Downloads: 8 This Week
    Last Update:
    See Project
  • 4
    Cactus

    Cactus

    Low-latency AI inference engine optimized for mobile devices

    Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. ...
    Downloads: 9 This Week
    Last Update:
    See Project
  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

    Learn how to protect your Microsoft 365 data, with simple, actionable tips today.

    Watch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
    Watch Demo Series
  • 5
    whisper.cpp

    whisper.cpp

    Port of OpenAI's Whisper model in C/C++

    whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently.
    Downloads: 681 This Week
    Last Update:
    See Project
  • 6
    Kimi K3 in C

    Kimi K3 in C

    A 2.78-trillion-parameter Kimi K3 running inference on a single CPU

    Kimi K3 in C is a portable C99 inference engine built to run the 2.78-trillion-parameter Kimi K3 model on CPUs without BLAS, machine-learning frameworks, or GPUs. It demonstrates inference from a roughly 1.56 TB checkpoint with measured memory use as low as 8.24 GB. The runtime streams model trunk layers and routed experts from disk instead of keeping all weights resident in memory. Memory presets balance pinned layers and an expert LRU cache for laptops, desktops, workstations, and servers. ...
    Downloads: 11 This Week
    Last Update:
    See Project
  • 7
    FLUX.2-klein-4B

    FLUX.2-klein-4B

    Flux 2 image generation model pure C inference

    FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. Because the implementation is in plain C and focuses on data locality and vectorized operations, flux2.c can be integrated into performance-critical code paths where control over memory layout and execution behavior matters, such as GPU kernels, embedded systems, or custom ML runtime engines.
    Downloads: 9 This Week
    Last Update:
    See Project
  • 8
    fairseq2

    fairseq2

    FAIR Sequence Modeling Toolkit 2

    fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a...
    Downloads: 10 This Week
    Last Update:
    See Project
  • 9
    Colibrì

    Colibrì

    Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine

    Colibri is a compact inference engine designed to run the 744-billion-parameter GLM-5.2 mixture-of-experts model on consumer hardware. It keeps the dense portion of the quantized model in memory while streaming routed experts from a large disk-based store as they are needed. The runtime is implemented in pure C, requires no Python or BLAS during inference, and can operate without a GPU. Compressed attention caches, expert caching, optional hot tiers, and speculative decoding reduce memory...
    Downloads: 18 This Week
    Last Update:
    See Project
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • 10
    QSMM

    QSMM

    An adaptive state model development framework.

    QSMM, a recursive acronym for "QSMM State Machine Model", is a framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior. The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 11
    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is...
    Downloads: 6 This Week
    Last Update:
    See Project
  • 12
    audioFlux

    audioFlux

    A library for audio and music analysis, feature extraction

    A library for audio and music analysis, and feature extraction. Can be used for deep learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training and is used to...
    Downloads: 11 This Week
    Last Update:
    See Project
  • 13
    dibnn

    dibnn

    Drop In the Bucket Neural Networks

    One more lightweight neural network in C.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 14
     SynaptaOS

    SynaptaOS

    Synapta OS is a preconfigured educational Linux distribution with AI

    🌐 Synapta OS Synapta OS is an educational Linux distribution preconfigured with local Artificial Intelligence (AI) capabilities. It is designed for schools and remote areas where Internet connectivity is limited or unavailable, offering access to AI-based learning and digital tools offline. Version 1.4.6
    Downloads: 4 This Week
    Last Update:
    See Project
  • 15
    Amoeba

    Amoeba

    Linux Command Line Learning Program

    Amoeba is a Linux command-line learning program that observes and adapts to the Linux command line storing learned strings and their usage data. It enhances command-line proficiency by capturing command outputs, adapting string lengths, and periodically saving knowledge. Sandboxing is essential for security, and optionally a virtual machine would further isolates it from the host system.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 16

    Faum

    Fast Autonomous Unsupervised Multidimiensional Classification

    This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 17
    The Algorithms - C #

    The Algorithms - C #

    Collection of various algorithms in mathematics, machine learning

    ...Contributors from around the world continually add new implementations and improvements, making the repository a collaborative learning project.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 18
    Llama 2 Everywhere (L2E)

    Llama 2 Everywhere (L2E)

    Llama 2 Everywhere (L2E)

    Llama 2 Everywhere (L2E) is an open-source implementation of the LLaMA-2 large language model architecture designed to demonstrate how transformer-based language models can be executed with extremely minimal code. The project focuses on simplicity and educational clarity by implementing inference for LLaMA-style models in a compact C program rather than relying on large machine learning frameworks. Developers can train models using a Python training pipeline and then run inference using a lightweight C implementation that requires very few dependencies. The architecture mirrors the structure of the LLaMA-2 model family, allowing compatible model checkpoints to be converted and executed within the simplified runtime environment. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 19
    SOD

    SOD

    An Embedded Computer Vision & Machine Learning Library

    SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well as commercial products. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 20
    Unitag is a language-independent Unicode-based part-of-speech tagging system. Written entirely in ANSI-compatible C, it should (in theory) compile on any OS, but has been tested on 32-bit Windows.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 21

    NGSpop

    NGSpop: identifying & visualizing sequence variation in deepvariant

    *NOTICE* The official software(NGSpop) will be updated soon, so please visit us in 2/29. Thank you.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 22
    MuJoCo-py

    MuJoCo-py

    mujoco-py allows using MuJoCo from Python 3

    mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated.
    Downloads: 7 This Week
    Last Update:
    See Project
  • 23
    libpostal

    libpostal

    A C library for parsing/normalizing street addresses around the world

    A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 24
    DeepMind Lab

    DeepMind Lab

    A customizable 3D platform for agent-based AI research

    ...The flag is omitted from the examples here for brevity, but it should be used for real training and evaluation where performance matters. DeepMind Lab ships with an example random agent in python/random_agent.py which can be used as a starting point for implementing a learning agent.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 25
    Speech Recognition in English & Polish

    Speech Recognition in English & Polish

    Speech recognition software for English & Polish languages

    Software for speech recognition in English & Polish languages. Basic versions of SkryBot: 1. SkryBot Home Speech (English Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesEnglish/InstalatorSkryBotHomeSpeechDemo-2.6.9.18117.exe/download 2. SkryBot DoMowy (Polish Language) - https://sourceforge.net/projects/skrybotdomowy/files/ReleasesPolish/InstalatorSkryBotDoMowyDemo-2.4.9.18117.exe/download More...
    Downloads: 3 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • 2
  • 3
  • 4
  • Next