Search Results for "learning classifier system" - Page 2

Showing 1043 open source projects for "learning classifier system"

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  • 1
    Porcupine

    Porcupine

    On-device wake word detection powered by deep learning

    Build always-listening yet private voice applications. Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux...
    Downloads: 5 This Week
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  • 2
    TensorFlow Lite for Microcontrollers

    TensorFlow Lite for Microcontrollers

    Infrastructure to enable deployment of ML models

    TensorFlow Lite for Microcontrollers is a TensorFlow Lite runtime designed for running machine learning models on tiny embedded devices. It targets microcontrollers, DSPs, and other resource-constrained hardware where memory, compute, and power are limited. The project enables on-device inference without depending on an operating system, standard C or C++ libraries, or dynamic memory allocation. It is useful for applications such as wake-word detection, sensor analysis, gesture recognition, anomaly detection, and small vision or audio models. ...
    Downloads: 6 This Week
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  • 3
    WiFi DensePose

    WiFi DensePose

    Turn WiFi signals into real-time human pose estimation and detection

    WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. ...
    Downloads: 44 This Week
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  • 4
    Weights and Biases

    Weights and Biases

    Tool for visualizing and tracking your machine learning experiments

    Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved...
    Downloads: 3 This Week
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  • 5
    TabPFN

    TabPFN

    Foundation Model for Tabular Data

    TabPFN is an open-source machine learning system that introduces a foundation model designed specifically for tabular data analysis. The model is based on transformer architectures and implements a prior-data fitted network that can perform supervised learning tasks such as classification and regression with minimal configuration. Unlike many traditional machine learning workflows that require extensive hyperparameter tuning and training cycles, TabPFN is pre-trained to perform inference directly on tabular datasets. ...
    Downloads: 0 This Week
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  • 6
    dm_control

    dm_control

    DeepMind's software stack for physics-based simulation

    DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based).
    Downloads: 0 This Week
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  • 7
    Karpathy

    Karpathy

    An agentic Machine Learning Engineer

    ...The system is tightly integrated with the Claude Scientific Skills ecosystem, enabling the agent to leverage specialized scientific and machine learning tools. It is intended primarily for research and experimentation with autonomous ML workflows rather than as a polished production platform. Overall, karpathy represents an early step toward fully automated machine learning engineering driven by agentic AI systems.
    Downloads: 1 This Week
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  • 8
    TensorLy

    TensorLy

    Tensor Learning in Python

    TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU.
    Downloads: 0 This Week
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  • 9
    SocratiCode

    SocratiCode

    Enterprise-grade (40m+ LOC) codebase intelligence

    SocratiCode is an AI-assisted learning tool that applies the Socratic method to programming education, guiding users through problem-solving rather than directly providing answers. It encourages critical thinking by asking structured questions that lead developers toward discovering solutions on their own. The system is designed to improve understanding of programming concepts through iterative reasoning and dialogue.
    Downloads: 13 This Week
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  • 10
    CUDA Containers for Edge AI & Robotics

    CUDA Containers for Edge AI & Robotics

    Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

    CUDA Containers for Edge AI & Robotics is an open-source project that provides a modular container build system designed for running machine learning and AI workloads on NVIDIA Jetson devices. The repository contains container configurations that package the latest AI frameworks and dependencies optimized for Jetson hardware. These containers simplify the deployment of complex machine learning environments by bundling libraries such as CUDA, TensorRT, and deep learning frameworks into reproducible container images. ...
    Downloads: 0 This Week
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  • 11
    C3

    C3

    The goal of CLAIMED is to enable low-code/no-code rapid prototyping

    C3 is an open-source framework designed to simplify the development and deployment of data science and machine learning workflows through reusable components and low-code development techniques. The framework focuses on enabling rapid prototyping while maintaining a path to production through automated CI/CD integration. CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators.
    Downloads: 12 This Week
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  • 12
    SwanLab

    SwanLab

    An open-source, modern-design AI training tracking and visualization

    ...SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems.
    Downloads: 19 This Week
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  • 13
    Volcano

    Volcano

    A Cloud Native Batch System (Project under CNCF)

    Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with.
    Downloads: 27 This Week
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  • 14
    Amazing-Python-Scripts

    Amazing-Python-Scripts

    Curated collection of Amazing Python scripts

    Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning exercises. The repository encourages community contributions, allowing developers to add their own scripts and improve existing ones through pull requests. ...
    Downloads: 1 This Week
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  • 15
    Paperless-ngx

    Paperless-ngx

    A community-supported supercharged version of paperless

    Paperless-ngx is a community-supported open-source document management system that transforms your physical documents into a searchable online archive so you can keep, well, less paper.
    Downloads: 34 This Week
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  • 16
    Final2x

    Final2x

    2^x Image Super-Resolution

    The tool is available for Windows x64/arm64, MacOS x64/arm64, and Linux x64, allowing users to enjoy the benefits of super-resolution regardless of their operating system. It offers a wide range of models that can be used to achieve different levels of super-resolution, allowing users to choose the one that best suits their specific needs. Users have the flexibility to specify the desired output size for their images, ranging from small enhancements to large-scale super-resolution. The tool...
    Downloads: 32 This Week
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  • 17
    Skills Service

    Skills Service

    SkillTree is a micro-learning gamification platform

    Skills Service is an open-source microservice developed by the NSA that provides gamified skills tracking for developers. It enables organizations to define, track, and reward skill acquisition and progress through a customizable and modular system. Developers earn points and levels by completing tasks or learning activities, with progress tracked via a web UI or REST API. It is designed to foster a culture of continuous learning, provide visual skill feedback, and promote user engagement within teams or educational settings.
    Downloads: 1 This Week
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  • 18
    Vearch

    Vearch

    A distributed system for embedding-based vector retrieval

    Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment.
    Downloads: 0 This Week
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  • 19
    AI Engineer Headquarters

    AI Engineer Headquarters

    A collection of scientific methods, processes, algorithms

    AI-Engineer-Headquarters is a comprehensive educational repository designed to help developers become advanced AI engineers through a structured learning path and practical system-building exercises. The project serves as a curated collection of resources, methodologies, and tools covering topics across the entire artificial intelligence development lifecycle. Rather than focusing only on theoretical knowledge, the repository emphasizes applied learning and encourages engineers to build real systems that incorporate machine learning, large language models, data pipelines, and AI infrastructure. ...
    Downloads: 0 This Week
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  • 20
    learnhouse

    learnhouse

    The Next-gen Open Source learning platform for everyone

    learnhouse is an open-source learning platform designed to help individuals and organizations create, manage, and deliver online educational content. The platform aims to provide a modern alternative to traditional learning management systems by combining collaborative tools, structured courses, and content publishing features within a single system. Built with modern web technologies such as TypeScript, the platform supports flexible content creation workflows that allow instructors to organize lessons, resources, and learning modules. ...
    Downloads: 1 This Week
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  • 21
    springcloud-learning

    springcloud-learning

    Build microservices with the Spring Cloud ecosystem

    springcloud-learning is a hands-on tutorial repository that walks Java developers through building microservices with the Spring Cloud ecosystem. It breaks concepts into small, runnable modules so you can focus on one capability at a time—service discovery, configuration management, gateway routing, fault tolerance, messaging, and observability. The code emphasizes practical integration with common infrastructure like Nacos/Eureka for registry, Nacos/Config Server for configuration,...
    Downloads: 0 This Week
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  • 22
    deepjazz

    deepjazz

    Deep learning driven jazz generation using Keras & Theano

    deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music.
    Downloads: 0 This Week
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  • 23
    AIDE ML

    AIDE ML

    AI-Driven Exploration in the Space of Code

    ...The framework is designed for experimentation and academic research into automated programming and machine learning optimization.
    Downloads: 13 This Week
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  • 24
    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....
    Downloads: 579 This Week
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  • 25
    DeepSpeed

    DeepSpeed

    Deep learning optimization library: makes distributed training easy

    DeepSpeed is an easy-to-use deep learning optimization software suite that enables unprecedented scale and speed for Deep Learning Training and Inference. With DeepSpeed you can: 1. Train/Inference dense or sparse models with billions or trillions of parameters 2. Achieve excellent system throughput and efficiently scale to thousands of GPUs 3. Train/Inference on resource constrained GPU systems 4.
    Downloads: 8 This Week
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