Chevron Left
Вернуться к First Steps in Linear Algebra for Machine Learning

Отзывы учащихся о курсе First Steps in Linear Algebra for Machine Learning от партнера Национальный исследовательский университет "Высшая школа экономики"

4.3
звезд
Оценки: 8
Рецензии: 2

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 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....

Лучшие рецензии

Фильтр по:

1–2 из 2 отзывов о курсе First Steps in Linear Algebra for Machine Learning

автор: Daniel H C

Mar 01, 2020

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

автор: Roger S

Feb 26, 2020

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

Not much course materials.