Hands-On Introduction to Transformers for Computer Vision

Explore the groundbreaking features of vision transformers in this robust machine learning course. Begin with the foundations of transformers and their revolutionary applications in computer vision. Learn how to implement vision transformers, uncover techniques for training and fine-tuning state-of-the-art models, and assess them using rigorous evaluation metrics. Efficiently deploy models using quantization to support edge environments and uncover insights. Observe firsthand the transition from theory to practice through real-world dataset applications. Gain insights into ensuring model safety and reliability through evaluation and debugging techniques. Whether you're an AI researcher, a data engineer, or a developer, this course equips you with the tools to excel in the rapidly evolving landscape of machine learning.

Learning objectives
Understand why and how transformers are so popular in CV.
Implement transformers in your own projects.
Fine-tune to improve model performance.
Add explainability for responsible AI models.
Take a deep dive in Vision Transformers.