need some general guidance on how to use market's clustering feature
Generated on 8/3/2024
1 search
To use the market's clustering feature in Create ML, you can follow the guidance provided in the "What’s new in Create ML" session from WWDC 2024. Here are some steps and tips based on the session:
-
Data Preparation:
- Ensure your data is well-prepared and annotated correctly. You can visualize and debug your annotations using the Create ML app to ensure they match your expectations. This is crucial for avoiding issues like duplicate predictions (What’s new in Create ML).
-
Feature Extraction:
- Extract valuable temporal information from your data. For example, you can use the date feature extractor component to extract features like the day of the week or the month of the year. This helps the model learn from specific trends in the data (What’s new in Create ML).
-
Building the Model:
- Use the time series forecaster model to predict future values based on historical data. This model is general-purpose and can be used for various types of data, such as sales or sensor data. You need to split your data into training and validation sets and decide on the prediction window (What’s new in Create ML).
-
Training and Validation:
- Train your model by providing it with a sufficient context of historical data. For example, if you want to forecast sales three days in the future, you might provide the last 15 days of historical data as context (What’s new in Create ML).
By following these steps, you can effectively use the market's clustering feature in Create ML to build and train models that can predict future trends based on historical data.
Relevant Sessions
If you need more specific guidance or have other questions, feel free to ask!
Meet FinanceKit
Learn how FinanceKit lets your financial management apps seamlessly and securely share on-device data from Apple Cash, Apple Card, and more, with user consent and control. Find out how to request one-time and ongoing access to accounts, transactions, and balances — and how to build great experiences for iOS and iPadOS.
Support semantic search with Core Spotlight
Learn how to provide semantic search results in your app using Core Spotlight. Understand how to make your app’s content available in the user’s private, on-device index so people can search for items using natural language. We’ll also share how to optimize your app’s performance by scheduling indexing activities. To get the most out of this session, we recommend first checking out Core Spotlight documentation on the Apple Developer website.
What’s new in Create ML
Explore updates to Create ML, including interactive data source previews and a new template for building object tracking models for visionOS apps. We’ll also cover important framework improvements, including new time-series forecasting and classification APIs.
Bring your machine learning and AI models to Apple silicon
Learn how to optimize your machine learning and AI models to leverage the power of Apple silicon. Review model conversion workflows to prepare your models for on-device deployment. Understand model compression techniques that are compatible with Apple silicon, and at what stages in your model deployment workflow you can apply them. We’ll also explore the tradeoffs between storage size, latency, power usage and accuracy.