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

Introduction

• Comparison of ML Kit, TensorFlow, and other machine learning services for government
• Overview of ML Kit features and components designed to support public sector workflows

Getting Started

• Setting up the ML Kit SDK for government applications
• Exploring APIs and sample apps tailored for government use cases

Implementing ML Kit Vision APIs

• Automating data entry through text recognition capabilities
• Detecting faces for secure identification in selfies and portraits
• Interpreting body positions for enhanced security and compliance
• Adding background effects to improve user experience in government applications
• Integrating barcode scanning for efficient data management
• Identifying objects, places, species, etc., using image labeling techniques
• Locating prominent objects in images to enhance situational awareness
• Recognizing handwritten texts with digital ink recognition for archival and documentation purposes

Working with Natural Language APIs

• Identifying languages to support multilingual communication in government services
• Translating texts to facilitate cross-cultural interactions within public sector operations
• Generating smart replies to improve efficiency in customer service and administrative tasks
• Using entity extraction for data analysis and compliance monitoring

Optimizing Existing Apps with ML Kit

• Utilizing custom models within the ML Kit framework to enhance government applications
• Migrating from Firebase to the new ML Kit SDK for improved performance and security
• Transitioning from Mobile Vision to ML Kit SDK for enhanced functionality and support
• Reducing app size for efficient deployment in government environments
• Refactoring apps to use dynamic feature modules for better resource management

Troubleshooting Tips

Summary and Next Steps