Скачать или смотреть 9-11. Practical Applications: Completeness & Hilbert Spaces (Linear Algebra for Data Science)

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【Linear Algebra for Data Science】
This course explains the knowledge of linear algebra, which is essential for data science enthusiasts, in an easy-to-understand way.

In this channel, you can obtain:
1. Intuitive understanding
2. Mathematical understanding
3. Practical understanding
of linear algebra for data science!

Many linear algebra concepts are abstract, and it is challenging to understand how they are applied in real-world data analytics. Lectures in this channel provide easy-to-understand explanations of various concepts of linear algebra in a way that is not only mathematically but also intuitively understandable. In addition, the lectures explain how each concept is useful in data analytics as a practical application.

Instructor: Takuma Kimura (木村 琢磨), Ph.D.
Scientist of Organizational Behavior and Business Analytics
https://orcid.org/0000-0001-7126-188X
  / takuma-kimura-ba6242104  

#linearalgebra #datascience #innerproduct #completeness #cauchysequences #hilbertspace #svm #supportvectormachine