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Introduction to Transformers

Offered By: Simons Institute via YouTube

Tags

Transformers Courses Machine Learning Courses Deep Learning Courses Neural Networks Courses Attention Mechanisms Courses Sequence to Sequence Models Courses Self-Attention Courses

Course Description

Overview

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Dive into a comprehensive lecture on the fundamentals of Transformer models, delivered by Daniel Hsu from Columbia University as part of the Special Year on Large Language Models and Transformers: Part 1 Boot Camp at the Simons Institute. Explore the architecture, mechanisms, and applications of these groundbreaking neural network models that have revolutionized natural language processing and beyond. Gain insights into the key components of Transformers, including self-attention and positional encoding, and understand their impact on various AI tasks. This 70-minute talk provides a solid foundation for both beginners and intermediate learners looking to grasp the core concepts behind one of the most influential innovations in modern machine learning.

Syllabus

Introduction to Transformers


Taught by

Simons Institute

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