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

Introduction

• Comparing ML Kit, 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 (Face Detection)
• Analyzing body positions (Pose Detection)
• Applying background effects (Selfie Segmentation)
• Integrating Barcode Scanning capabilities
• Identifying objects, locations, species, etc. (Image Labeling)
• Locating prominent objects within an image (Object Detection and Tracking)
• Recognizing handwritten text (Digital Ink Recognition)

Working with Natural Language APIs

• Identifying languages
• Translating texts
• Generating smart replies
• Utilizing entity extraction

Optimizing Existing Apps with ML Kit

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

Troubleshooting Tips

Summary and Next Steps