# Turi-Create
**Repository Path**: mirrors/Turi-Create
## Basic Information
- **Project Name**: Turi-Create
- **Description**: 这一框架应该会让开发者更容易构建机器学习模型
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 10
- **Forks**: 6
- **Created**: 2017-12-10
- **Last Updated**: 2025-09-06
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
Quick Links: [Installation](#supported-platforms) | [Documentation](#documentation)
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# Turi Create
Turi Create simplifies the development of custom machine learning models. You
don't have to be a machine learning expert to add recommendations, object
detection, image classification, image similarity or activity classification to
your app.
* **Easy-to-use:** Focus on tasks instead of algorithms
* **Visual:** Built-in, streaming visualizations to explore your data
* **Flexible:** Supports text, images, audio, video and sensor data
* **Fast and Scalable:** Work with large datasets on a single machine
* **Ready To Deploy:** Export models to Core ML for use in iOS, macOS, watchOS, and tvOS apps
With Turi Create, you can accomplish many common ML tasks:
| ML Task | Description |
|:------------------------:|:--------------------------------:|
| [Recommender](https://apple.github.io/turicreate/docs/userguide/recommender/) | Personalize choices for users |
| [Image Classification](https://apple.github.io/turicreate/docs/userguide/image_classifier/) | Label images |
| [Drawing Classification](https://apple.github.io/turicreate/docs/userguide/drawing_classifier) | Recognize Pencil/Touch Drawings and Gestures |
| [Sound Classification](https://apple.github.io/turicreate/docs/userguide/sound_classifier) | Classify sounds |
| [Object Detection](https://apple.github.io/turicreate/docs/userguide/object_detection/) | Recognize objects within images |
| [One Shot Object Detection](https://apple.github.io/turicreate/docs/userguide/one_shot_object_detection/) | Recognize 2D objects within images using a single example |
| [Style Transfer](https://apple.github.io/turicreate/docs/userguide/style_transfer/) | Stylize images |
| [Activity Classification](https://apple.github.io/turicreate/docs/userguide/activity_classifier/) | Detect an activity using sensors |
| [Image Similarity](https://apple.github.io/turicreate/docs/userguide/image_similarity/) | Find similar images |
| [Classifiers](https://apple.github.io/turicreate/docs/userguide/supervised-learning/classifier.html) | Predict a label |
| [Regression](https://apple.github.io/turicreate/docs/userguide/supervised-learning/regression.html) | Predict numeric values |
| [Clustering](https://apple.github.io/turicreate/docs/userguide/clustering/) | Group similar datapoints together|
| [Text Classifier](https://apple.github.io/turicreate/docs/userguide/text_classifier/) | Analyze sentiment of messages |
Example: Image classifier with a few lines of code
--------------------------------------------------
If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code:
```python
import turicreate as tc
# Load data
data = tc.SFrame('photoLabel.sframe')
# Create a model
model = tc.image_classifier.create(data, target='photoLabel')
# Make predictions
predictions = model.predict(data)
# Export to Core ML
model.export_coreml('MyClassifier.mlmodel')
```
It's easy to use the resulting model in an [iOS application](https://developer.apple.com/documentation/vision/classifying_images_with_vision_and_core_ml):