Introduction: Solving data science challenges with mathematics

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Получаемые навыки

Eigenvalues And Eigenvectors, Basis (Linear Algebra), Transformation Matrix, Linear Algebra

Рецензии

4.7 (оценок: 11,085)

  • 5 stars
    74,66 %
  • 4 stars
    19,80 %
  • 3 stars
    3,41 %
  • 2 stars
    1,15 %
  • 1 star
    0,95 %

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.

Из урока

Introduction to Linear Algebra and to Mathematics for Machine Learning

Преподаватели

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    David Dye

    Professor of Metallurgy

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    Samuel J. Cooper

    Associate Professor

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    A. Freddie Page

    Strategic Teaching Fellow

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