Machine Learning for Engineering & Science Applications | IIT Madras - #7 Matrix Operations Special Matrices Matrix Decompositions

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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22 learners

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 07 10 18 12 18 Machine Learning for Engineering and Science Applications Balaji Srinivasan Nptel Online Course Lecture New Lecture Lecture - 07

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! This lecture explores advanced matrix operations, special types of matrices, and matrix decompositions, specifically focusing on Eigen decomposition. It explains the concept of Eigenvalues and Eigenvectors, highlighting their significance in understanding the behavior of linear transformations represented by matrices. The lecture aims to provide a comprehensive overview of essential matrix concepts used in machine learning. 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 #MatrixOperations #SpecialMatrices #MatrixDecompositions #EigenDecomposition #Eigenvalues #Eigenvectors

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