Building and Training Your Own Custom Image Recognition AI

Overview

Learn to build and train custom image recognition models using Cognitive Services, enabling identification of specific objects in photographs without extensive coding.

Syllabus

• Introduction to Image Recognition
Overview of Image Recognition and AI
Importance and Applications in Various Industries
Course Objectives and Outcomes
• Getting Started with Cognitive Services
Introduction to Microsoft Cognitive Services
Setting Up a Cognitive Services Account
Overview of Available Image Recognition APIs
• Data Collection and Preparation
Identifying Your Image Dataset Requirements
Techniques for Collecting Image Data
Image Preprocessing and Augmentation
Organizing and Labeling Images for Model Training
• Building Custom Image Recognition Models
Introduction to Transfer Learning
Setting Up Your Development Environment
Selecting and Training Pre-trained Models
Customizing Models for Specific Object Recognition
• Training Your Image Recognition Model
Understanding Basic Training Parameters
Implementing Training Loops and Evaluation Metrics
Handling Overfitting and Underfitting
• Deployment and Integration
Exporting and Deploying Your Model
Integrating with Applications via APIs
Performance Optimization in Different Environments
• Testing and Validation
Creating a Testing Dataset
Model Validation Techniques and Metrics
Iterative Improvement Based on Testing Feedback
• Ethical Considerations and Best Practices
Addressing Bias in Image Recognition AI
Ensuring Privacy and Data Protection
Best Practices for Responsible AI Usage
• Conclusion and Project Showcase
Summary of Key Learnings
How to Keep Improving and Updating Models
Student Project Presentations and Feedback Sessions
• Additional Resources and Continued Learning
Recommended Books, Articles, and Online Courses
Community Forums and Professional Networks

Subjects

Conference Talks