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M4ML - Linear Algebra - 5.4 Calculating eigenvectors
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Welcome to the “Mathematics for Machine Learning: Linear Algebra” course, offered by Imperial College London.
Week 5, Video 4 - Calculating eigenvectors
Your course instructors are
If you have any questions about the course, please contact the instructors via Twitter.
This course offers an introduction to the linear algebra required for common machine learning techniques. We start by looking at some simultaneous equations problems and showing how these can be expressed using vectors and matrices. We then move on to exploring vector spaces and see how these can be reformulated by changing basis. Next, we explore some methods for manipulating matrices and see how this is done using code, before moving on to some special cases shown using interactive animations. In the final module, we bring all the concepts together to recreate Google’s famous PageRank algorithm, which uses eigenvectors to rank search result by their connectivity.
This course was designed to help you quickly build an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck; it is not intended to cover all the details. We hope you enjoy it and that it gives you the confidence to dive into one of the many other wonderful machine learning courses available online!
Week 5, Video 4 - Calculating eigenvectors
Your course instructors are
If you have any questions about the course, please contact the instructors via Twitter.
This course offers an introduction to the linear algebra required for common machine learning techniques. We start by looking at some simultaneous equations problems and showing how these can be expressed using vectors and matrices. We then move on to exploring vector spaces and see how these can be reformulated by changing basis. Next, we explore some methods for manipulating matrices and see how this is done using code, before moving on to some special cases shown using interactive animations. In the final module, we bring all the concepts together to recreate Google’s famous PageRank algorithm, which uses eigenvectors to rank search result by their connectivity.
This course was designed to help you quickly build an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck; it is not intended to cover all the details. We hope you enjoy it and that it gives you the confidence to dive into one of the many other wonderful machine learning courses available online!
0:08:45
M4ML - Linear Algebra - 5.7 Introduction to PageRank
0:04:25
M4ML - Linear Algebra - 5.2 What are eigenvalues and eigenvectors?
0:10:08
M4ML - Linear Algebra - 5.4 Calculating eigenvectors
0:05:55
M4ML - Linear Algebra - 1.1 Introduction: Solving data science challenges with mathematics
0:09:06
M4ML - Linear Algebra - 1.3 Getting a handle on vectors
0:05:32
M4ML - Linear Algebra - 3.1 Matrices, vectors, and solving simultaneous equation problems
0:09:54
M4Ml - Linear Algebra - 4.1 Einstein summation convention and the symmetry of the dot product
0:10:37
M4ML - Linear Algebra - 3.4 Determinants and inverses
0:08:39
M4ML - Linear Algebra - 3.3 Part 2: Going from Gaussian elimination to finding the inverse matrix
0:04:14
M4ML - Linear Algebra - 2.4 Part 1: Basis, vector space, and linear independence
0:01:06
M4ML - Linear Algebra - 1.5 Summary
0:11:29
M4ML - Linear Algebra - 1.4 Operations with vectors
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M4ML - Linear Algebra - 3.3 Part 1: Solving the apples and bananas problem: Gaussian elimination
0:07:27
M4ML - Linear Algebra - 5.6 Eigenbasis example
0:05:53
M4ML - Linear Algebra - 5.5 Changing to eigenbasis
0:01:15
M4ML - Linear Algebra - 5.8 Summary
0:04:38
M4ML - Linear Algebra - 4.2 Part 2: Doing a transformation in a changed basis
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M4ML - Linear Algebra - 2.5 Summary
0:03:31
M4ML - Linear Algebra - 1.2 Motivations for linear algebra
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M4ML - Linear Algebra - 3.5 Summary
0:03:33
M4ML - Linear Algebra - 5.3 Special eigen-cases
0:01:57
M4ML - Linear Algebra - Wrap up of this Linear Algebra course
0:05:42
M4ML - Linear Algebra - 3.2 Part 1: How matrices transform space
0:41:23
Linear Algebra - Math for Machine Learning
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