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EPFLx: Optimization: principles and algorithms – Unconstrained nonlinear optimization

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Duration

6 weeks

Pacing

Self-paced

Pricing

Free

Category:

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

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About this course

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

At a Glance:
Institution: EPFLx
Subject: Math
Level: Introductory
Prerequisites:
The course assumes no prior knowledge of optimization. It relies heavily on linear algebra, analysis and calculus (matrices, derivatives, eigenvalues, etc.)
The knowledge of the programming language Python is an asset to learn the details of the algorithms. However, it is possible to follow the course without programming at all.
Language: English
Video Transcript: English
Associated skills:Algorithms, Nonlinear Programming

What You’ll Learn:
About this course

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

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EPFLx: Optimization: principles and algorithms – Unconstrained nonlinear optimization
EPFLx: Optimization: principles and algorithms – Unconstrained nonlinear optimization
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