Machine Learning for Engineering & Science Applications | IIT Madras - #19 Introduction to Constrained Optimization | Unconstrained Optimization

Unlock the Future: Master AI & Machine Learning with NPTEL-IITM’s Comprehensive Course! Dive into Neural Networks, Deep Learning, Probabilities, and Optimization Techniques tailored for Engineering & Science Applications. Your AI journey starts here!

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What you'll learn

Understand the historical development and foundational concepts of artificial intelligence.
Gain proficiency in applying machine learning techniques to engineering and science problems.
Develop skills in using linear algebra and calculus for machine learning modeling.
Learn to implement and optimize machine learning algorithms using Python packages.

This course includes

32 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Lecture 19

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! Building upon the previous lecture on unconstrained optimization, this lecture provides a concise introduction to constrained optimization. It explains the concept of optimizing functions subject to mathematical constraints, offering a brief overview of how constrained optimization works. The lecture aims to familiarize viewers with the general ideas and principles of constrained optimization. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #ConstrainedOptimization #OptimizationTechniques #MathematicalConstraints

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