Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device. Core ML optimizes on-device performance by leveraging the CPU, GPU, and Neural Engine while minimizing its memory footprint and power consumption. Running a model strictly on the user’s device removes any need for a network connection, which helps keep the user’s data private and your app responsive.

Core ML tools contains all supporting tools for Core ML model conversion, editing and validation. This includes deep learning frameworks like TensorFlow, PyTorch, Keras, Caffe as well as classical machine learning frameworks like LIBSVM, scikit-learn, and XGBoost.

With coremltools, you can do the following:

• Convert trained models from frameworks like TensorFlow and PyTorch to the Core ML format.
• Read, write, and optimize Core ML models.
• Verify conversion/creation (on macOS) by making predictions using Core ML.

To get the latest version of coremltools:

pip install --upgrade coremltools

For the latest changes please see the release notes.

• User Guides and Examples
• Core ML Specification
• API Reference