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Вернуться к Mathematics for Machine Learning: Linear Algebra

Отзывы учащихся о курсе Mathematics for Machine Learning: Linear Algebra от партнера Имперский колледж Лондона

4.7
звезд
Оценки: 9,099
Рецензии: 1,842

О курсе

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....

Лучшие рецензии

CS
31 мар. 2018 г.

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

EC
9 сент. 2019 г.

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.

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226–250 из 1,841 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Jaromir S

30 сент. 2019 г.

I needed a quick refresh of my prior knowledge of linear algebra for my MSc course and I wasnt disappointed. I also appreciated the complementary python exercises and the effort to put the material into a context of a real world application.

автор: Someindra K S

3 янв. 2019 г.

I got a lot of intuition about some fundamental aspects of linear algebra. Rest of courses on maths was very rigorous in terms of methods. This was more inclined towards applications in machine learning. I enjoyed the entire learning process

автор: Stefan B

8 апр. 2018 г.

It was fun to work through the course. Sometimes it was challenging as it has to be. Now I have a much better understanding of the topic. Especially appreciated is the approach of the instructors to build intuition: it worked for me, thanks!

автор: Souvik G

8 февр. 2021 г.

I have never visioned mathematics the way it was taught here. I believe every Engineer may he/she be a an ML engineer or not must take this course to just fall in love of mathematics. This course will inherently motivate you to dig deeper.

автор: Danilo d C P

19 июля 2019 г.

I really enjoyed taking this course. I could review and learn for the first time some important topics for machine learning, in special the eigenvalues and eigenvectors classes. I'd like to thank the course's professors and collaborators.

автор: Omar R G

17 мар. 2019 г.

An excellent course on the fundamentals of linear algebra. It was great revisiting all this topics. I would also say that some knowledge on linear algebra would be useful for taking this course given the fact that the lectures are quick.

автор: Felipe C

29 нояб. 2020 г.

Very good course. I liked it a lot. Some abstract thinking required. The last week is a bit less well explained but OK nonetheless.

In my experience, the estimated times for completing the work are a bit optimistic, it took me more time.

автор: Abdul-Rashid B

6 янв. 2021 г.

Great lecturers, excellent delivery of subject matter. This course did not disappoint me. It provides a concise yet in-depth revision of linear algebra as is relevant to machine learning. Looking forward to more from these instructors.

автор: dhiraj b

21 апр. 2020 г.

Offered the much needed perspective of linear algebra to develop actual understanding, than just solving problems without understanding why and how actual computation works. I would like to thank the professors for such a great course.

автор: Duraivelu K

11 апр. 2020 г.

This course not only provided me the fundamental knowledge of Mathematics required to learn my next interested course of Machine Learning, but also helped me to kill the lockdown period due to covid-19 pandemic in a useful way at home.

автор: AKSHAT M

19 июля 2020 г.

Excellent course. Outstanding methodology. Great fun and intuition based leaning, kudos to David Dye, Sam Cooper and the ICL team. Thank you very much for bringing forward this course. Looking forward for many more courses from ICL :D

автор: Greg E

15 июля 2019 г.

I thoroughly enjoyed this course. After using matrices and vectors for decades in my work, I have finally gained some intuition about what the dot-product operation, determinant and eigen-vectors actually represent. Thank you so much.

автор: Jafed E G

6 июля 2019 г.

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

автор: Mark A C

22 нояб. 2020 г.

This course has provided me a better understanding of linear algebra concepts specifically on how eigenvalues, eigenvectors, matrices, and vectors can actually be observed or used in engineering (or even in day to day) applications.

автор: Vijayakumar

20 мая 2020 г.

It was a very good learning and I enjoyed a lot. Hoping to take the advanced level courses in Machine learning and related areas. Thank you very much Professors David dye, Samuel J Cooper and A Freddie Page. Hoping to see you again.

автор: laszlo

21 апр. 2018 г.

Awesome course!!! The course is very helpful for those who are willing to build an intuition of linear algebra. The coding assignments are a bit easy for CS students, but allow you to understand what has been taught in the course.

автор: David S

23 июня 2019 г.

Excellent. Exactly what I needed. A linear algebra course in machine learning. Top notch presentations, materials, and explanations. A nice blend of concepts and detailed calculations especially in transformations and eigenvectors.

автор: Shwetha T R

14 сент. 2020 г.

I loved this course! Both Prof David Rye and Prof Sam Cooper were amazing and used brilliant techniques to ensure creative learning. I enjoyed the eigen vectors and values and pagerank algo module a little too much! Thanks a lot!

автор: PATHIRAJA M P H S

12 июля 2020 г.

The course contains very creative introductions to some of the linear algebra theories that I was already familiar with. Could get new intuitions and better, deeper understanding of those concepts. Really glad I took this course.

автор: Mohamed S

26 июня 2020 г.

I liked the course and huge number of exercises. Maybe my only problem is the academic form of the lectures that makes me lost sometimes and forces me to google for an Indian guy who can teach me the concept in a more easier way.

автор: Rahul S

28 окт. 2019 г.

This course is little challenging if one has not revised Linear Algebra before, but quite interesting and fun given the examples and utility only after learning the basics of linear algebra elsewhere and then attempting this one.

автор: Liam M

4 апр. 2018 г.

This is an excellent refresher of vectors and linear algebra, and although I did it years ago in college I still found some new insights from doing this course. Its all explained very well without being bogged down in formailty.

автор: Rohan A

9 июня 2020 г.

Great course guys! I have done a course on Linear Algebra in my university and watched the 3Blue1Brown series on Essence on Linear Algebra. This course was a good recap of the concepts and their applications in machine learning

автор: Ramy S R

27 сент. 2020 г.

Excellent course. Material is explained thoroughly through concise short videos with plenty of visualizations that make linear algebra intuitive. Assignments are chosen carefully and the curated python labs are very enjoyable.

автор: Prateek K S

28 мая 2018 г.

Nice course. This course is very good to build your fundamental knowledge for machine learning. This course gave me very clean and straight forward understand how mathematics play very important role in machine learning field.