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: 9,563
Рецензии: 1,928

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

PL
25 авг. 2018 г.

Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.

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.

Фильтр по:

1626–1650 из 1,920 отзывов о курсе Mathematics for Machine Learning: Linear Algebra

автор: Alex G

14 июня 2020 г.

Went a bit too quickly for me towards the end of the course (coming into this as a layman), otherwise very good.

автор: Jordan W

14 янв. 2020 г.

Fantastic course. My favourite delivery of Linear Algebra thus far. Both Sam and David were a joy to learn from.

автор: Unfunny C

21 дек. 2019 г.

The course is very comprehensive and yet is very focused towards actual application of LA in Data Science and ML

автор: Walter S

9 февр. 2021 г.

Very good course overall. I would have liked more explanation on the exercises and more time working on python.

автор: Saurabh G

7 нояб. 2019 г.

This is one of the most important courses for someone who wants to build career in the machine learning field.

автор: Shriniwas S U

10 мая 2020 г.

Good course but Instructor should provide some lectures on python programing which is related to assignments.

автор: Rodney N d S

31 авг. 2018 г.

This course is short, you can conclude it in a month, but you will learn a lot with the assignments in Python

автор: Chakola P J

23 авг. 2020 г.

The course provided a good insight into some of the essential concepts with respect to vectors and matrices!

автор: Ronast S

18 янв. 2020 г.

This course provides basic insights about vectors and matrices and their analysis in multidimensional space.

автор: Patricio Á R

3 авг. 2020 г.

Permite ver claramente lo que potencialmente se puede lograr con la aplicación de los conceptos aprendidos.

автор: Diego C

4 июля 2020 г.

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

автор: Meixin Z

10 дек. 2018 г.

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

автор: Shubham K

31 авг. 2019 г.

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

автор: Akwila F

10 сент. 2020 г.

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

автор: José D

15 сент. 2018 г.

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

автор: Stylianos V

26 июля 2020 г.

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

автор: Harry L

8 апр. 2020 г.

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

автор: Prashant D

16 февр. 2019 г.

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

автор: Alvaro I S

22 мая 2018 г.

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

автор: Eduardo V O

19 авг. 2020 г.

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

автор: 李振宇

20 янв. 2020 г.

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

автор: sai s

17 мар. 2019 г.

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

автор: Ng K

8 окт. 2020 г.

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

автор: Dr. H K L

5 мая 2020 г.

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

автор: Ajay R

11 сент. 2019 г.

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