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 via Text Recognition.
• Detecting faces for selfies and portraits (Face Detection).
• Interpreting body positions (Pose Detection).
• Adding background effects (Selfie Segmentation).
• Integrating Barcode Scanning.
• Identifying objects, locations, species, etc. (Image Labeling).
• Locating prominent objects within an image (Object Detection and Tracking).
• Recognising handwritten texts (Digital Ink Recognition).

Working with Natural Language APIs

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

Optimising Existing Applications with ML Kit

• Using custom models with ML Kit.
• Migrating from Firebase to the new ML Kit SDK.
• Migrating from Mobile Vision to the ML Kit SDK.
• Reducing application size for deployment.
• Refactoring applications to utilise dynamic feature modules.

Troubleshooting Tips

Summary and Next Steps