Integrate machine learning models into your app.
- iOS 11.0+
- macOS 10.13+
- tvOS 11.0+
- watchOS 4.0+
- Mac Catalyst 13.0+Beta
With Core ML, you can integrate machine learning models into your app.
A model is the result of applying a machine learning algorithm to a set of training data. You can use a model to make predictions based on new input data. For example, a model trained on a region’s historical house prices may be able to predict a house’s price when given the number of bedrooms and bathrooms.
You can train a model with Create ML. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Core ML also allows you to retrain or fine-tune an existing model on-device with
MLUpdate, keeping your users’ data private and secure.
Core ML is the foundation for domain-specific frameworks and functionality. Core ML supports Vision for image analysis, Natural Language for natural language processing, Speech for converting audio to text, and SoundAnalysis for identifying sounds in audio. Core ML itself builds on top of low-level primitives like Accelerate and BNNS, as well as Metal Performance Shaders.
Core ML is optimized for on-device performance, which minimizes its memory footprint and power consumption. Running strictly on the device ensures the privacy of user data and guarantees that your app remains functional and responsive when a network connection is unavailable.