Directorio de skills
Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.
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.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
scikit-learn: machine learning in Python
Deep Learning for humans
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Visualizer for neural network, deep learning and machine learning models
The fastai deep learning library
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
A game theoretic approach to explain the output of any machine learning model.
Directorio de skills
Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.
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.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
scikit-learn: machine learning in Python
Deep Learning for humans
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Visualizer for neural network, deep learning and machine learning models
The fastai deep learning library
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
A game theoretic approach to explain the output of any machine learning model.
Directorio de skills
Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.
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.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
scikit-learn: machine learning in Python
Deep Learning for humans
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Visualizer for neural network, deep learning and machine learning models
The fastai deep learning library
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
A game theoretic approach to explain the output of any machine learning model.
Directorio de skills
Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.
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.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
scikit-learn: machine learning in Python
Deep Learning for humans
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Visualizer for neural network, deep learning and machine learning models
The fastai deep learning library
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
A game theoretic approach to explain the output of any machine learning model.