Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.
scikit-learn: machine learning in Python
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Visualizer for neural network, deep learning and machine learning models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A game theoretic approach to explain the output of any machine learning model.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.
scikit-learn: machine learning in Python
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Visualizer for neural network, deep learning and machine learning models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A game theoretic approach to explain the output of any machine learning model.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.
scikit-learn: machine learning in Python
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Visualizer for neural network, deep learning and machine learning models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A game theoretic approach to explain the output of any machine learning model.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
An Open Source Machine Learning Framework for Everyone
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.
scikit-learn: machine learning in Python
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Visualizer for neural network, deep learning and machine learning models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A game theoretic approach to explain the output of any machine learning model.