core-ml

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Core ML, Create ML, Vision framework, Natural Language framework, on-device ML integration. Use when user wants image classification, text analysis, object detection, sound classification, model optimization, or custom model integration. Covers Core ML vs Foundation Models decision.

AI & Automation 565 stars 47 forks Updated 4 days ago MIT

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Skill Content

# Core ML Skills Combined advisory, generator, and workflow skill for integrating machine learning into Apple platform apps. Covers Core ML model integration, Vision framework image analysis, NaturalLanguage framework text processing, Create ML training, and on-device model optimization. ## When This Skill Activates Use this skill when the user: - Wants to add ML capabilities to their app - Needs to integrate a Core ML model (.mlmodel) into an Xcode project - Wants to use the Vision framework for image analysis (faces, text recognition, body pose, object detection) - Wants to use the NaturalLanguage framework for text processing (sentiment, entities, language detection) - Needs to train a custom model with Create ML - Wants to optimize a model for on-device use (quantization, pruning, palettization) - Needs to choose between Core ML and Foundation Models (Apple Intelligence) - Asks about image classification, object detection, sound classification, or tabular data prediction - Wants real-time camera + ML processing ## Decision Guide: Core ML vs Foundation Models Before generating code, determine which framework is appropriate. ### Use Foundation Models (Apple Intelligence) When: - You need general-purpose text generation, summarization, or conversational AI - Target is iOS 26+ / macOS 26+ (Foundation Models requires Apple Silicon + latest OS) - The task is open-ended language understanding or generation - You want `@Generable` structured output from natural language - S...

Details

Author
rshankras
Repository
rshankras/claude-code-apple-skills
Created
9 months ago
Last Updated
4 days ago
Language
Swift
License
MIT

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