Machine Learning for Engineering & Science Applications | IIT Madras - #5 Norms | Machine Learning for Engineering & Science Applications

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

Norms Lecture 05 09 10 12 18 Machine Learning for Engineering and Science Applications Balaji Srinivasan Nptel Online Course Lecture New Lecture Lecture - 05

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! This lecture delves into the concept of norms in linear algebra, explaining their significance in quantifying vector magnitudes and measuring distances. It covers different types of norms, such as the L1 and L2 norms, and discusses their applications in machine learning, including regularization techniques. The lecture aims to provide a thorough understanding of norms and their role in various machine learning algorithms. 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 #Norms #LinearAlgebra #VectorMagnitude #DistanceMeasurement #Regularization #MachineLearning

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