Optimization Crash Course
Offered By: Simons Institute via YouTube
Course Description
Overview
Dive into a comprehensive 42-minute lecture on optimization techniques presented by Ashia Wilson from MIT as part of the Geometric Methods in Optimization and Sampling Boot Camp. Explore key topics including motivation, algorithms, convexity, optimality, projections, and lower bounds. Gain insights into explicit examples, algebra, quadratic functions, and gradient descent methods. Enhance your understanding of optimization principles and their practical applications in this informative talk from the Simons Institute.
Syllabus
Introduction
Topics
Motivation
Algorithms
Convexity
Optimality
Projections
Lower Bounds
Explicit Example
Algebra
Quadratic
Gradient Descent
Taught by
Simons Institute
Related Courses
Practical Predictive Analytics: Models and MethodsUniversity of Washington via Coursera Deep Learning Fundamentals with Keras
IBM via edX Introduction to Machine Learning
Duke University via Coursera Intro to Deep Learning with PyTorch
Facebook via Udacity Introduction to Machine Learning for Coders!
fast.ai via Independent