YoVDO

Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 7

Offered By: International Centre for Theoretical Sciences via YouTube

Tags

Deep Learning Courses Data Analysis Courses Machine Learning Courses Neural Networks Courses Transformers Courses High-Energy Physics Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore advanced machine learning techniques in this lecture focusing on Deepsets, Graph Neural Networks, and Transformers. Delve into the application of these powerful algorithms in the context of High Energy Physics research. Gain insights from expert Sanmay Ganguly as he discusses the potential of these methods for analyzing complex data structures and improving data-driven discoveries in particle physics. Learn how these cutting-edge approaches can be leveraged to process the massive datasets generated by experiments like the Large Hadron Collider, potentially uncovering new physics phenomena and advancing our understanding of the universe.

Syllabus

Lectures on Deepsets, Graph Neural Network and Transformers... (Lecture 7) by Sanmay Ganguly


Taught by

International Centre for Theoretical Sciences

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn Statistical Learning with R
Stanford University via edX Machine Learning 1—Supervised Learning
Brown University via Udacity Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX