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What Is the Create ML Framework?
Learn about Create ML and how to get started building models today
Create ML is Apple’s latest addition to a robust suite of first-party development tools.
Starting in WWDC17, which I had the opportunity to attend on scholarship, Apple unveiled Core ML — their first-party ML framework to enable ML models to be embedded into iOS and macOS apps seamlessly. Create ML, both a framework and an application, was unveiled a year later at WWDC18.
Per the Core ML documentation, Core ML serves the purpose of “integrating machine learning models into your app.” That’s great! But what if you’re an iOS developer by training and don’t have any Python/TensorFlow skills to create models yourself? Well, Create ML serves as a complement for that.
Create ML’s documentation states that Create ML’s purpose is “creating machine learning models for use in your app.” So now there is an end-to-end pathway for iOS and macOS developers to create models for use in their applications.
What Kinds of Models Can Be Created in Create ML?
Create ML supports five different categories of models:
- Image
- Sound
- Motion
- Text
- Table
Within Image, users can make classification and detection models. Sound and Motion support just classification. Text supports classification and tagging. Table supports creating classifier, regressor, and recommender models.
Just How Easy Is It to Make a Model in Create ML?
To demonstrate, I’m going to create an Image classification model to classify whether an image is a cat or dog.
With Create ML opened, I created a new Image Classifier project:
On my first model source, what is called for me MyImageClassifier 1, I will be uploading a folder containing all of my training data. The folder I uploaded is called test and has this…
