Search Results for "learning" - Page 26
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Showing 1643 open source projects for "learning"
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PyOpenCL
OpenCL integration for Python, plus shiny features
...PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and machine learning workflows that demand acceleration. -
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Potpie
Create custom engineering agents for your codebase
Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding. -
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nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
...These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. It is designed to work with various AI tools and command-line agents, making it highly flexible and extensible. ClawTeam also includes monitoring tools such as dashboards and tmux-based views to observe agent activity and progress. -
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ARIS
Lightweight Markdown-only skills for autonomous ML research
...It also highlights the potential of autonomous agents to handle repetitive or exploratory tasks that would otherwise require significant human effort. The framework is particularly relevant for developers interested in automated experimentation, continuous learning systems, and AI-driven productivity. -
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Ultralytics
Ultralytics YOLO
Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. The framework supports a full end-to-end workflow, including dataset preparation, model training, evaluation, and export to various deployment formats. Its architecture emphasizes performance optimization, balancing speed and accuracy to support real-time applications across industries. Ultralytics also provides pretrained models and flexible configuration options, allowing users to adapt the system to different datasets and use cases with minimal effort. -
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Sunfish
Sunfish: a Python Chess Engine in 111 lines of code
...It includes a simple UCI-compatible interface, allowing it to be integrated with graphical chess interfaces or used in terminal-based gameplay. The codebase is intentionally minimal, making it ideal for experimentation, modification, and learning purposes. -
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AnyTool
AnyTool: Universal Tool-Use Layer for AI Agents
...It uses progressive filtering and adaptive orchestration to ensure the right tools are retrieved efficiently and work cohesively with agents of varying complexity, scaling to thousands of tools with self-optimizing behavior. The system also tracks tool reliability and quality, offering a safer and more predictable automation experience with persistent learning from previous executions. -
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Unicorn
The magical reactive component framework for Django
Quickly add in simple interactions to regular Django templates without learning a new templating language. Stop fighting with a new JavaScript build tool and separate process to use yet another frontend framework. Building a feature-rich API is complicated. Skip creating a bunch of serializers and just use Django. Unicorn progressively enhances a normal Django view, so the initial render of components is fast and great for SEO. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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HelloGitHub
Share interesting, entry-level open source projects on GitHub
HelloGitHub shares interesting, entry-level open source projects on GitHub. It is updated and released in the form of a monthly magazine on the 28th of every month. The content includes interesting, entry-level open-source projects, open-source books, practical projects, enterprise-level projects, etc., so that you can feel the charm of open source in a short time and fall in love with open source! At first, I just wanted to collect interesting, high-quality, and easy-to-use projects that I... -
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Sprix SAGE Router
State-aware SELF/COLLABORATE/HANDOFF routing for A2A agent networks
Sprix SAGE Router is an open-source routing layer for coordinating agents in Agent2Agent networks. It decides whether an active agent should continue alone, recruit collaborators, or hand a task to another specialist. Routing decisions account for current progress, capability coverage, context-transfer costs, permissions, budgets, and deadlines. The system assigns remaining requirements to agents through task dependency graphs and estimates execution schedules. It learns contextual... -
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Ditto
The simplest self-building coding agent
...The project is intentionally lightweight and experimental, making it easier to understand than larger agentic coding platforms. Its modular structure separates generated Flask components into cleaner directories for routes, templates, and static files. It is best suited for prototyping, learning, and exploring how natural-language app generation can work in a small local project. -
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LinuxPlay
An open-source, ultra-low-latency remote desktop for Linux hosts
...The project demonstrates how to build a media player from scratch, including handling audio-video synchronization and playback controls. It supports local file playback and may include streaming capabilities depending on configuration. LinuxPlay is structured as both a functional tool and a learning resource for developers interested in multimedia systems. Its design emphasizes simplicity and performance, avoiding unnecessary dependencies. Overall, it serves as a practical example of media player implementation on Linux. -
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All-in-RAG
Big Model Application Development Practice 1
All-in-RAG is an open-source educational project designed to teach developers how to build applications using retrieval-augmented generation techniques. The repository provides a structured learning path that covers both theoretical foundations and practical implementation steps for RAG systems. It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. The project also explores advanced topics such as hybrid retrieval methods, query optimization, and evaluation techniques for improving system accuracy. ... -
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SimpleLLM
950 line, minimal, extensible LLM inference engine built from scratch
SimpleLLM is a minimal, extensible large language model inference engine implemented in roughly 950 lines of code, built from scratch to serve both as a learning tool and a research platform for novel inference techniques. It provides the core components of an LLM runtime—such as tokenization, batching, and asynchronous execution—without the abstraction overhead of more complex engines, making it easier for developers and researchers to understand and modify. Designed to run efficiently on high-end GPUs like NVIDIA H100 with support for models such as OpenAI/gpt-oss-120b, Simple-LLM implements continuous batching and event-driven inference loops to maximize hardware utilization and throughput. ... -
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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. -
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Ariadne
Python library for implementing GraphQL servers
...Ariadne enables Python developers to use a schema-first approach to the API implementation. This is the leading approach used by the GraphQL community and supported by dozens of frontend and backend developer tools, examples, and learning resources. Ariadne makes all of this immediately available to you and other members of your team. Ariadne offers a small, consistent, and easy to memorize API that lets developers focus on business problems, not the boilerplate. Ariadne was designed to be modular and open for customization. If you are missing or unhappy with something, extend or easily swap with your own. ... -
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. By solving progressively... -
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Dask
Parallel computing with task scheduling
...It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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OpenSRE
Build your own AI SRE agents. The open source toolkit for the AI era
OpenSRE is an open-source framework designed to build AI-powered Site Reliability Engineering agents that automate incident investigation and root cause analysis across modern cloud environments. It connects to observability tools, infrastructure systems, and communication platforms to gather logs, metrics, and traces in real time. When an alert is triggered, the system autonomously analyzes correlated signals, identifies anomalies, and generates structured investigation reports with... -
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves consistency in redaction tasks. ... -
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Hugging Face - Speech To Speech
Open speech-to-speech models and pipelines by Hugging Face toolkit AI
This project from Hugging Face focuses on enabling direct speech-to-speech processing using modern machine learning models. It provides tools and reference implementations that allow audio input to be transformed into audio output without requiring an intermediate text representation. Hugging Face - Speech To Speech builds on recent advances in speech modeling, combining components such as speech recognition, translation, and synthesis into unified pipelines. -
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Claude Code Skills & Plugins Hub
270+ Claude Code plugins with 739 agent skills
Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and... -
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Cradle framework
The Cradle framework is a first attempt at General Computer Control
Cradle is an open-source framework designed to enable AI agents to perform complex computer tasks by interacting with software environments in a way similar to human users. The system introduces the concept of General Computer Control, where AI agents receive screenshots as input and perform actions through simulated keyboard and mouse operations. This approach allows agents to interact with any software interface without relying on specialized APIs or predefined automation scripts. The... -
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FireRed-Image-Edit
General-purpose image editing model that delivers high-fidelity
...It is built on a flexible text-to-image foundation model that has been extended with training paradigms including pretraining, supervised fine-tuning, and reinforcement learning to imbue the system with strong instruction following and editing consistency. The model excels in maintaining visual and text stylistic fidelity, allowing users to preserve the original artistic qualities of an image while applying creative changes according to natural language instructions. In addition to editing single images, FireRed supports multi-image editing scenarios such as virtual try-on or batch transformations, making it suitable for both creative and practical workflows.
