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Вернуться к First Steps in Linear Algebra for Machine Learning

Отзывы учащихся о курсе First Steps in Linear Algebra for Machine Learning от партнера НИУ ВШЭ

4.1
звезд
Оценки: 121
Рецензии: 22

О курсе

The main goal of the course is to explain the main concepts of linear algebra that are used in data analysis and machine learning. Another goal is to improve the student’s practical skills of using linear algebra methods in machine learning and data analysis. You will learn the fundamentals of working with data in vector and matrix form, acquire skills for solving systems of linear algebraic equations and finding the basic matrix decompositions and general understanding of their applicability. This online course is suitable for you if you are not an absolute beginner in Matrix Analysis or Linear Algebra (for example, have studied it a long time ago, but now want to take the first steps in the direction of those aspects of Linear Algebra that are used in Machine Learning). Certainly, if you are highly motivated in study of Linear Algebra for Data Sciences this course could be suitable for you as well. This Course is part of HSE University Master of Data Science degree program. Learn more about the admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/rj64e....

Лучшие рецензии

AG
24 июля 2020 г.

with great assignments,one could get relation of LA with computer science.For naive english it could hurdles at first.but nice content.must for intermediatory

EA
30 дек. 2020 г.

This is a well designed course, with the right balance of theory and practice. The quizzes and programming assignments reinforce the material effectively.

Фильтр по:

1–22 из 22 отзывов о курсе First Steps in Linear Algebra for Machine Learning

автор: Alagu P P G

25 июля 2020 г.

with great assignments,one could get relation of LA with computer science.For naive english it could hurdles at first.but nice content.must for intermediatory

автор: Daniel H

1 мар. 2020 г.

The material was very well presented, and the exercises were helpful for learning

автор: k v r

15 апр. 2020 г.

poor presenation

автор: Olivio A C J

4 сент. 2020 г.

It is a good course. It mixes theory and practice with Python in a right way and I could learn/review a lot. It has also the right amount of coursework. It is always a pleasure to study using the courses from Coursera. As a lifelong learner I want to be permanently engaged in online courses, from Coursera, EdX ou Youtube. It is the future of Education.

автор: Eduardo A

31 дек. 2020 г.

This is a well designed course, with the right balance of theory and practice. The quizzes and programming assignments reinforce the material effectively.

автор: Kevin A G D

8 авг. 2020 г.

I learnt a lot with this course, good introduction to linear algebra, and good guidance to the use of sk-learn for Machine Learning.

автор: Georgios P

30 янв. 2021 г.

Bad Presentation and dead forum!

автор: Xingxing T

8 апр. 2020 г.

The program is really useful for exploring machine learning. I appreciate that the math involved are so relevant to SVM, even though I am BA major and do not have strong math background. I just need put enough time and go through each example. That's where I find this course very suitable. Plenty examples to explain the concepts.

автор: Alex C

7 февр. 2021 г.

A really nice course, i learnt a lot...the practical at the end was hard but good. I had to google a lot to find some nice tutorials to follow at medium! Would have been nice if that was a little easier with some easier python building up to the project! but learning by doing etc.

автор: Carlos M V R

21 июля 2020 г.

This is a great courses, sometimes explanations could be better but in general is awesome and they teach us good applications of linear algebra in the field of machine learning. I would like to rate this course with 4.5, but Coursera does not allow us to rate in that way.

автор: Elkin E G A

5 апр. 2021 г.

You can improve a little bit your teacher's English. Still, I could find yet something this deep on algebra and machine learning on Coursera. It was worth taking.

автор: Malikaharris

19 февр. 2021 г.

I don't want to do this one anymore

автор: Moloko M

6 авг. 2021 г.

Great, Great course! The course makes it easy to connect the theory of Linear Algebra and applied Machine Learning. I would recommend it to those who have taken an undergrad Linear Algebra course and want to apply that knowledge to something meaningful such as Machine learning.

автор: Ruthlyn N V

5 июня 2020 г.

The programming assignments were really challenging! I thought I'm not gonna pass this course since it's my first time to encounter Python language. Thank you so much Prof. Piontkovski and Prof. Chernyshev for the new learnings :)

автор: James N

23 мар. 2021 г.

Quite challenging but necessary to have a deeper understanding of machine learning algorithms

автор: Ivan A T U

25 июля 2021 г.

Me gustan la matemáticas, pero combinar la programación es cosa de locos, genial este curso.

автор: Julio C D M

13 апр. 2021 г.

Excellent course. It explains really good the Linear Algebra fundamentals for ML

автор: Peter

18 июля 2021 г.

G​ood overview over the topic. Could be one or two week longer. Liked it.

автор: Tan Z

24 апр. 2020 г.

Good, but have few examples and exercises.

автор: Hanif N

28 мар. 2021 г.

i've passed. thanks

автор: Roger S

26 февр. 2020 г.

Very conventional and theoretical way of presenting the stuff. There are some Python exercises, though.

Not much course materials.

автор: Karen H

28 мар. 2021 г.

Guys, you need to master English or talk in Russian. It is really difficult to follow.