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Showing 14907 open source projects for "x-windows"
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including... -
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ML-NLP
This project is a common knowledge point and code implementation
ML-NLP is a large open-source repository that collects theoretical knowledge, practical explanations, and code examples related to machine learning, deep learning, and natural language processing. The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training... -
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ML Retreat
Machine Learning Journal for Intermediate to Advanced Topics
ML Retreat is an open-source learning repository that serves as a structured journal documenting advanced topics in machine learning and artificial intelligence. The project compiles detailed notes, technical explanations, and curated resources that guide readers through complex concepts across modern AI research. Rather than functioning as a traditional tutorial series, the repository is organized as a learning journey that progressively explores increasingly advanced subjects. Topics... -
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LLMSurvey
A Survey of Large Language Models
LLMSurvey is an open-source research repository that aggregates academic papers, resources, and references related to large language models. The project is closely associated with the academic survey titled “A Survey of Large Language Models,” which provides a comprehensive overview of the development, architecture, capabilities, and societal implications of modern LLMs. The repository organizes hundreds of research papers into thematic sections that reflect the main areas of LLM research,... -
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Karpathy
An agentic Machine Learning Engineer
karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. The system is tightly integrated with... -
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alive-progress
A new kind of Progress Bar, with real-time throughput, ETA
alive-progress is an advanced Python progress bar library that introduces a highly animated and adaptive approach to tracking long-running tasks. Unlike traditional static progress indicators, it dynamically adjusts spinner speed and visual feedback based on actual throughput, giving users a more intuitive sense of activity. The library is designed with performance efficiency in mind, using multithreaded updates that minimize CPU overhead and terminal noise. It includes sophisticated ETA... -
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List of independent blogs in Chinese
List of independent blogs in Chinese
List of independent blogs in Chinese is a curated open repository that aggregates and maintains a large list of independent Chinese-language blogs across technology, design, and personal knowledge domains. The project aims to promote the independent blogging ecosystem by making it easier for readers to discover high-quality personal sites outside major content platforms. It is community-driven, allowing contributors to submit and update blog entries so the directory remains current and... -
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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... -
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Claude Code Hooks Mastery
Master Claude Code Hooks
Claude Code Hooks Mastery is a trending community-centric GitHub repository aimed at helping developers master Claude Code hooks — customizable integration points that let users extend, automate, and augment workflows when using Claude Code, an agentic terminal coding assistant. Although the project itself doesn’t include a single coherent application, it functions as a curated collection of advanced hook examples, best practices, and coding patterns that show how to tailor Claude Code to... -
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Auto-Deep-Research
Your Fully-Automated Personal AI Assistant
Auto-Deep-Research is a system designed to fully automate deep research workflows using language models, retrieval, planning, and multi-stage reasoning to produce structured research artifacts such as surveys, benchmarks, reports, and even prototypes without heavy human intervention. Users provide a research topic or multifaceted goal, and the system autonomously breaks the objective down into subtasks like literature collection, critical summarization, cross-comparison, citation extraction,... -
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VideoRAG
"VideoRAG: Chat with Your Videos
VideoRAG is a retrieval-augmented generation (RAG) framework tailored for video content that enables AI systems to answer questions, summarize, and reason over long videos by combining visual embeddings with contextual search. The system works by first breaking video into clips, extracting visual and audio-textual features, and indexing them into embeddings, then using an LLM with a retriever to pull relevant segments on demand. When a user query is received, VideoRAG locates semantically... -
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SCAIL
Towards Studio-Grade Character Animation via In-Context Learning of 3D
SCAIL is a project developed by the ZAI Organization, focusing on AI-driven research initiatives. While specific documentation about SCAIL’s exact goals and implementation is limited from the repository context alone, the project appears to be part of a collection of machine learning and AI research tools that facilitate scalable model development, evaluation, or application workflows. Given its listing alongside other ZAI projects like speech recognition and text-to-speech systems, SCAIL... -
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TurboDiffusion
100–200× Acceleration for Video Diffusion Models
TurboDiffusion is an advanced open-source framework designed to dramatically accelerate video diffusion model generation, aiming for performance improvements on the order of 100–200× compared with traditional implementations while retaining high output quality. It achieves this by combining a suite of algorithmic and engineering optimizations, including attention acceleration techniques, efficient step distillation methods, and quantization strategies that reduce computational overhead. The... -
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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... -
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bu-agent-sdk
An agent is just a for-loop
The bu-agent-sdk from the Browser Use project is a minimalistic Python framework that defines an AI agent as a simple loop of tool calls, aiming to keep abstractions low so developers can build autonomous agents without unnecessary complexity. At its core, the agent loop repeatedly queries a large language model, interprets its output, and executes defined “tools” — functions annotated with task names — to perform actions, allowing the agent to complete tasks like arithmetic,... -
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Manim Skills Repository
Agent skills for Manim to create 3Blue1Brown style animations
Manim Skills Repository provides a well-crafted set of “agent skills” and reusable components that make it easier to produce animations in Manim similar to the iconic style seen in 3Blue1Brown videos. It supplies templates, best-practice patterns, and example scenes that help users quickly get started with both Manim Community Edition and the older ManimGL framework, allowing for expressive mathematical and conceptual animations without reinventing the wheel. The project aims to wrap common... -
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python-socketio
Python Socket.IO server and client
python-socketio is a robust Python library that implements the Socket.IO protocol, enabling real-time, bidirectional communication between web clients and servers. It works with multiple asynchronous frameworks such as asyncio, eventlet, and gevent, so developers can choose the concurrency model that best fits their application needs while still using a consistent API. The library provides both server and client implementations, allowing Python applications to serve and communicate with... -
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Moondream
Tiny vision language model
Moondream is a creative code project and visual experimentation repository that explores generative graphics, aesthetic patterns, and interactive art through code. The project typically showcases procedural visualizations, algorithmic designs, and artistic experiments that push the boundaries of what can be expressed with programming languages and rendering frameworks. While the exact nature can vary by commit or branch, Moondream’s work often blends geometry, color theory, and motion to... -
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MyPy
Optional static typing for Python
mypy is a static type checker for Python that analyzes source code without executing it, catching type errors early in development. It implements PEP 484-style type hints and supports gradual typing, allowing untyped or partially typed modules to coexist with statically typed code. The tool integrates with common editors and CI systems, and offers a daemon mode for fast, incremental checks across large codebases. Advanced configuration via mypy.ini or pyproject.toml enables per-module... -
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OpenMLSys-ZH
Machine Learning Systems: Design and Implementation
This repository is the Chinese translation (or localization) of the OpenMLSys project documentation. Its aim is to make the technical content, tutorials, architecture descriptions, and user guides of the OpenMLSys system more accessible to Chinese-speaking users. The repo mirrors the structure of the original OpenMLSys docs: sections on system design, API references, deployment instructions, module overviews, and example workflows. It helps bridge language barriers in open machine learning... -
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Meta Agents Research Environments (ARE)
Meta Agents Research Environments is a comprehensive platform
Meta Agents Research Environments (ARE) is a simulation and benchmarking platform. It is designed to evaluate AI agents in dynamic, evolving, multi-step tasks. Unlike static benchmarks, ARE supports environments where agents must adapt to changes over time and reason over sequences of actions. It interacts with applications and faces uncertainty. The included Gaia2 benchmark offers 800 scenarios across multiple “universes”. It can test reasoning, memory, tool use, and adaptability.... -
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TorchDistill
A coding-free framework built on PyTorch
torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this... -
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TruLens
Evaluation and Tracking for LLM Experiments
TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack-agnostic... -
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Optax
Optax is a gradient processing and optimization library for JAX
Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize... -
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Haiku Sonnet for JAX
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX's pure function transformations. Haiku provides two core tools: a module abstraction, hk.Module, and a...
