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Mathematics for Machine Learning: Linear Algebra

Course Cover

5

(8)

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Course Features

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Duration

19 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

19 hours

Course Description

Linear Algebra is a course that will teach you what linear algebra looks like and how it connects with vectors or matrixes. Next we'll look at vectors and matrixes, their functions, and the tricky issue of eigenvalues. We will then discuss how to use them in solving problems. Then, we will discuss how they can be used to have fun with datasets such as how to rotate faces and extract eigenvectors to see how the Pagerank algorithm operates.

As we aim for data-driven apps, we will be using code to implement some ideas. This course will introduce you to Jupyter notebooks as well as code blocks in Python. These will not be long and will focus on the concepts. They will also help you if your code is new. This course will help you to understand vectors and matrixes. This course will help you bridge the gap between machine learning and linear algebra.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Eigenvalues And Eigenvectors

Transformation Matrix

How to rotate images of faces

How the Pagerank algorithm works

Course Instructors

David Dye

Professor of Metallurgy

David Dye is a Professor of Metallurgy in the Department of Materials. He develops alloys for jet engines, nuclear and caloric materials so as to reduce fuel burn and avoid in-service failure. This i...

Samuel J. Cooper

Associate Professor

Dr Sam Cooper is an Associate Professor in energy science and materials design in the Dyson School of Design Engineering at Imperial College London. His PhD was on the characterisation and optimisati...

A. Freddie Page

Strategic Teaching Fellow

Dr Freddie Page is the Strategic Teaching Fellow in the Dyson School of Design Engineering, Imperial College London. He graduated with a MPhys from the University of Oxford in 2011 and got his PhD in...

Course Reviews

Average Rating Based on 8 reviews

4.9

88%

13%

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