Back to Mathematics for Machine Learning: Linear Algebra

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9,931 ratings

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1,995 reviews

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.
Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before.
At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

EC

Sep 9, 2019

Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.

NS

Dec 22, 2018

Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.

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By Diego C

•Jul 4, 2020

This course is a very good opportunity to introduce to the main concepts of linear algebra for data science

By Meixin Z

•Dec 10, 2018

the content of this course is really clear, but the assignment system about program needs to be improved.

By Shubham K

•Aug 31, 2019

The course is great with really good teaching community , as a beginner it was a really good experience.

By Akwila F

•Sep 10, 2020

Perfect for anyone who wants to take specialization but not recommended for beginners in linear algebra

By José D

•Sep 15, 2018

Good video & subtitles for non-english speaker, practical examples, good introduction to linear algebra

By Stylianos V

•Jul 26, 2020

Very good course for an introduction in linear algebra with many useful concepts for machine learning

By Harry L

•Apr 8, 2020

Excellent syllabus and lectures. However, a detail explanation of each practice quiz should be given.

By Prashant D

•Feb 16, 2019

Good explanation. Some of the exercises and quizzes need a deeper understanding of the course content

By Alvaro I S

•May 22, 2018

Great course! I have learned about linear algebra, some geometry, and a bit of programming in Python.

By Eduardo V O

•Aug 19, 2020

Course is great. It can improve showing some more complex examples, similar to the ones in the tests

By 李振宇

•Jan 20, 2020

Good experience for a beginner like me, and I am looking forward to completing the rest two courses!

By sai s

•Mar 17, 2019

A very basic introduction to the math that you will find in Machine Learning. Beginner level Course

By Ng K

•Oct 8, 2020

the 2nd half part of the eigenvectors is a bit fragmented and could be given one more week on it.

By Dr. H K L

•May 5, 2020

it is good, and very use full to any one, if those are in teaching field as a mathematics teacher

By Ajay R

•Sep 11, 2019

Tough course, but got better understanding of topics related to math behind real-world ML models.

By Ahmed O H

•Jan 29, 2020

It's not perfect, but I hope if the last of the specialization is more practicable and flexible.

By Sudeep P

•Jun 2, 2020

I am really happy with the course as it helped me to understand the core concept of algortihms.

By Hamza F

•Mar 24, 2020

A well constructed course that can address students coming from different academic backgrounds.

By Marwa A E K

•Oct 18, 2019

I learned and developed intuition of the concepts covered in this course, which I'm happy with.

By Berkay E

•Jul 26, 2019

Some of the concepts are unclear. You need to make extra research to understand whole concepts.

By Liang Y

•Apr 16, 2019

Very good I learn a lot though I get confused in Week 4 about E @ TE @ inv(E). Thank you profs!

By Vinayaka R K

•Aug 15, 2020

The eigwn vector parts could've been much much better, rest apart assignments were really good

By Mohamed A A

•Jun 23, 2020

very good for beginners who want to understand what happens in machine learning under the hood

By Md. M I

•May 3, 2020

A little more assignments might be good towards the end. Otherwise, it is an excellent course.

By Alexander D K

•Aug 21, 2019

Fairly good introductory course but not a substitution for a proper LA course for ML purposes.

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