Vision Transformer from Scratch Tutorial
Demo
About this course
In this comprehensive course, Tunga Barak guides you in building a Vision Transformer from the ground up, exploring key concepts such as patch embeddings, multi-head attention, and the construction of a full Transformer model. You'll also gain insights into the comparison of Vision Transformers with models like CLIP and SIGP, paving the way for understanding how AI models process visual data effectively.
What you should already know
Prior knowledge of machine learning concepts and familiarity with basic programming is required before taking the course.
What you will learn
By the end of the course, learners will have a thorough understanding of Vision Transformers and their applications in image processing, enabling them to build and implement their own models.