Machine Learning for Mobile Apps using Google’s ML Kit Training Course

Introduction

• Comparing ML Kit with TensorFlow and other machine learning services.
• Overview of ML Kit features and components.

Getting Started

• Setting up the ML Kit SDK.
• Exploring APIs and sample applications.

Implementing ML Kit Vision APIs

• Automating data entry through Text Recognition.
• Detecting faces for selfies and portraits via Face Detection.
• Interpreting body positions using Pose Detection.
• Adding background effects with Selfie Segmentation.
• Integrating Barcode Scanning.
• Identifying objects, places, species, etc., through Image Labeling.
• Locating prominent objects in an image using Object Detection and Tracking.
• Recognizing handwritten texts via Digital Ink Recognition.

Working with Natural Language APIs

• Identifying languages.
• Translating texts.
• Generating smart replies.
• Using entity extraction.

Optimizing Existing Apps with ML Kit

• Utilizing custom models with ML Kit.
• Migrating from Firebase to the new ML Kit SDK.
• Migrating from Mobile Vision to the ML Kit SDK.
• Reducing app size for deployment.
• Refactoring apps to use dynamic feature modules.

Troubleshooting Tips

Summary and Next Steps