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Volver a First Steps in Linear Algebra for Machine Learning

Opiniones y comentarios de aprendices correspondientes a First Steps in Linear Algebra for Machine Learning por parte de HSE University

4.1
estrellas
121 calificaciones
22 reseña

Acerca del Curso

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....

Principales reseñas

AG
24 de jul. de 2020

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 de dic. de 2020

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

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1 - 22 de 22 revisiones para First Steps in Linear Algebra for Machine Learning

por Alagu P P G

25 de jul. de 2020

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

por Daniel H

1 de mar. de 2020

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

por k v r

15 de abr. de 2020

poor presenation

por Olivio A C J

4 de sep. de 2020

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.

por Eduardo A

31 de dic. de 2020

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

por Kevin A G D

8 de ago. de 2020

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

por Georgios P

30 de ene. de 2021

Bad Presentation and dead forum!

por Xingxing T

8 de abr. de 2020

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.

por Alex C

7 de feb. de 2021

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.

por Carlos M V R

21 de jul. de 2020

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.

por Elkin E G A

5 de abr. de 2021

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.

por Malikaharris

19 de feb. de 2021

I don't want to do this one anymore

por Moloko M

6 de ago. de 2021

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.

por Ruthlyn N V

5 de jun. de 2020

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 :)

por James N

23 de mar. de 2021

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

por Ivan A T U

25 de jul. de 2021

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

por Julio C D M

13 de abr. de 2021

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

por Peter

18 de jul. de 2021

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

por Tan Z

24 de abr. de 2020

Good, but have few examples and exercises.

por Hanif N

28 de mar. de 2021

i've passed. thanks

por Roger S

26 de feb. de 2020

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

Not much course materials.

por Karen H

28 de mar. de 2021

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