Building Scalable AI Computer Vision Applications
Offered By: Open Data Science via YouTube
Course Description
Overview
Explore a comprehensive 41-minute talk on building scalable AI computer vision applications. Learn about standardized processes and workflows to accelerate development for both application developers and data scientists. Discover techniques for preparing datasets, efficient annotation, model selection, benchmarking, and deployment considerations. Gain insights into extracting poor-performing data, monitoring model quality, and understanding key metrics for computer vision applications. Delve into the challenges of production deployment and learn how to leverage recent advancements in AI and machine learning for various computer vision use cases.
Syllabus
Introduction
Questions
Who am I
Advancements
Format of Data
Data Generation
Annotation
Model Selection
Optimization
Benchmarking
Deployment
Monitoring
Summary
Taught by
Open Data Science
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Computational Photography
Georgia Institute of Technology via Coursera Einführung in Computer Vision
Technische Universität München (Technical University of Munich) via Coursera Introduction to Computer Vision
Georgia Institute of Technology via Udacity