Introduction to Visual Foundation Models Course¶

Welcome to the "Introduction to Visual Foundation Models" course! This course is designed to provide a comprehensive overview of visual foundation models, their architectures, training methodologies, and applications in various computer vision tasks.

Course Structure¶

The course is divided into four main chapters:

1. What are Visual Foundation Models?

   • Overview of visual foundation models
   • Key characteristics and capabilities
   • Comparison with traditional computer vision models

2. How are Visual Foundation Models Built?

   • Architectural components
   • Training methodologies
   • Data requirements and preprocessing

3. Parameter-Efficient Fine-Tuning

   • Techniques for fine-tuning large models
   • Case studies and practical examples

4. Distillation of Visual Foundation Models

   • Knowledge distillation techniques
   • Benefits and challenges
   • Applications in resource-constrained environments

Getting Started¶

To get started with the course, navigate through the chapters using the sidebar. Each chapter contains detailed explanations, code examples, and practical exercises to reinforce your understanding.

Happy Learning!