One Shot Lecture–5 | Transformer (Derivation + Numerical) | 6 Marks Confirmed | BEE | SPPU

This is an academic lecture video that delves deeply into the Transformer model. The lecture is presented by Sir Ajit More, covering the basic concepts, formula derivation, and numerical analysis of Transformer. The course explains the application and principles of this algorithm in the field of deep learning in a detailed and easy-to-understand manner, making it a very valuable resource for anyone looking to gain a deeper understanding of Transformer and its role in practical applications. Key highlights include the fundamental principles of Transformer, the mathematical derivation of its formulas, and how to use these concepts in programming in practice. The lecture is both in-depth and accessible, suitable for scholars with a certain foundation in deep learning to reinforce their knowledge, as well as for beginners who wish to learn and master the Transformer algorithm. Target audience: This lecture is aimed at anyone interested in deep learning, particularly the Transformer model, including undergraduates, graduates, industry developers, and amateur enthusiasts with an interest in AI technology. For students preparing for exams related to BEE (Bharat Energy Exchange) or SPPU (Savitribai Phule Pune University), the content of this lecture is particularly important. Viewing recommendations: It is recommended that viewers have a basic understanding of neural networks and the fundamental concepts of Transformer before watching to better grasp the lecture content. The lecture is approximately one hour long, and viewers are advised to stay focused to fully grasp the key points.