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apple/turicreate

★ 11,175C++Audience · developerComplexity · 3/5Setup · moderate

TLDR

Apple's Python toolkit for building machine learning models without needing to know the math, trains image classifiers, sound recognizers, and recommenders in a few lines of code and exports them as Core ML files ready for iOS or macOS apps.

Mindmap

mindmap
  root((turicreate))
    What it does
      No-math ML training
      Core ML export
      Apple platform ready
    Supported Tasks
      Image classification
      Sound classification
      Activity recognition
      Recommendations
      Sentiment analysis
    Tech Stack
      Python
      C++ backend
      Core ML format
    Platforms
      macOS
      Linux
      iOS and watchOS apps
    Audience
      iOS developers
      Mobile app builders
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Things people build with this

USE CASE 1

Train an image classifier in five lines of Python and export it as a Core ML model to drop directly into your iOS app.

USE CASE 2

Build a sound classifier or activity recognizer from sensor data for an Apple Watch or iPhone app without writing any ML math.

USE CASE 3

Add personalized recommendations to your app, like suggested products or content, using Turi Create's recommendation task.

USE CASE 4

Analyze the sentiment of user-written text reviews inside a macOS or iOS app without a third-party API.

Tech stack

PythonC++Core MLpip

Getting it running

Difficulty · moderate Time to first run · 30min

Apple GPU acceleration is automatic on macOS, Linux GPU support requires a separate setup guide included in the repository.

No license information stated in the explanation.

In plain English

Turi Create is a Python toolkit from Apple that lets you build machine learning models without needing to understand the underlying math or algorithms. You work with tasks, not theory: tell it you want to classify images, and it handles the rest. The output is a model file in Apple's Core ML format, which you can drop directly into an iOS, macOS, watchOS, or tvOS app. The toolkit covers a wide range of common tasks. You can train a model to recognize objects in photos, classify sounds, detect activities from sensor data, group similar images, analyze the sentiment of text, or build a recommendation system that personalizes choices for users. Each task has its own simple function, and the README shows that a working image classifier can be written in about five lines of Python. Turi Create runs on macOS, Linux, and Windows (via the Windows Subsystem for Linux). It does not require a graphics card, though certain tasks run significantly faster when one is available. Apple GPU acceleration on macOS is automatic. On Linux, enabling GPU support requires following a separate guide included in the repository. Installation is done through Python's standard package manager with a single pip command. Apple recommends using a virtual environment to keep the package isolated from your other Python projects. The documentation includes a full user guide and API reference hosted on Apple's developer site.

Copy-paste prompts

Prompt 1
Using Apple's Turi Create, write a complete Python script that trains an image classifier on my custom image folder and exports it as a Core ML model I can use in Xcode.
Prompt 2
I want to add a sound classifier to my iOS app. Walk me through using Turi Create to train a model on audio files and export the resulting Core ML file.
Prompt 3
Show me how to build a simple recommendation system with Turi Create that takes a list of user-item interactions and outputs personalized suggestions.
Prompt 4
I'm on macOS, walk me through installing Turi Create in a virtual environment and running the five-line image classification example from scratch.
Prompt 5
How do I enable GPU acceleration for Turi Create on Linux? Walk me through the steps described in the separate GPU setup guide.
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