Overview
Discover Snap Search, a mobile AI project that enables visual search capabilities through innovative networking and mobile technology.
Syllabus
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- Course Introduction
- Overview of Snap Search Course Objectives
- Introduction to Capstone Project Requirements
- Fundamentals of Mobile AI
- Understanding AI Concepts for Mobile Devices
- Key Technologies in Mobile AI (e.g., Machine Learning Models, Edge AI)
- Visual Search Technologies
- Principles of Visual Recognition and Computer Vision
- Image Processing Techniques
- Overview of Current Visual Search Applications
- Networking Concepts for Mobile AI
- Basics of Mobile Networking
- Cloud vs Edge Computing for AI Applications
- Networking Protocols and Data Transmission in Mobile AI
- Building Snap Search - Application Architecture
- Defining Application Requirements and Use Cases
- System Design and Architecture for Snap Search
- User Interface and Experience Considerations
- Implementation of Visual Search on Mobile
- Integrating AI Models into Mobile Applications
- Image Data Handling and Privacy Considerations
- Performance Optimization Techniques for Mobile AI
- Advanced Topics in Mobile AI and Networking
- Machine Learning Model Deployment on Mobile
- Challenges and Solutions in Mobile Network Connectivity
- Testing and Evaluation
- Testing Mobile AI Applications for Accuracy and Performance
- User Testing and Feedback Integration
- Capstone Project Development
- Group Project Work Sessions
- Milestone Reviews and Feedback
- Final Presentation and Demonstration
- Preparing the Final Presentation
- Live Demonstration of Snap Search Application
- Course Review and Future Directions
- Review of Key Learnings
- Exploring Future Trends in Mobile AI and Networking
- Career Pathways in Mobile AI and Networking Fields
Taught by
Tags
On-Demand
