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Back to Linear Algebra for Machine Learning and Data Science

Learner Reviews & Feedback for Linear Algebra for Machine Learning and Data Science by DeepLearning.AI

4.6
stars
1,971 ratings

About the Course

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you鈥檒l apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. After completing this course, you will be able to: 鈥� Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc. 鈥� Apply common vector and matrix algebra operations like dot product, inverse, and determinants 鈥� Express certain types of matrix operations as linear transformations 鈥� Apply concepts of eigenvalues and eigenvectors to machine learning problems Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.聽 We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you鈥檒l use....

Top reviews

NA

Jun 18, 2023

Very visual and application oriented and gives the context for machine learning and where linAL is applied in PCA and neural networks. The structure is really byte sized and fun to work with.

SP

Jul 27, 2023

This course is truly exceptional for individuals eager to strengthen their grasp of Linear Algebra concepts, paving the way for a deeper understanding of machine learning and data science.

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226 - 250 of 481 Reviews for Linear Algebra for Machine Learning and Data Science

By Nackeeran N

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Aug 11, 2024

Very good course, well structured, easy to follow

By Yuganshu

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Feb 4, 2024

society needs more mathematics teachers like him!

By Jaeyong 鈥� L

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Feb 18, 2024

The programming assignments really helped a lot.

By 袗薪写褉褨泄 啸

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Mar 22, 2023

good explanation of linear algebra fundamentals.

By Nicolas F

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Aug 25, 2024

Incredible teaching method: clear and intuitive

By Kashif K

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May 21, 2023

Best ever courses i have done, very informative

By Joe S

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Oct 13, 2024

very helpful to grasp concepts and apply them

By Alan H

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Mar 12, 2023

The teacher is the best I've had on 糖心vlog官网观看.

By Francesco

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Jun 12, 2024

Really a good course with a lot of examples!

By Prince A A

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Feb 5, 2024

very educative. simplified complex concepts.

By chalapathi t

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Jun 7, 2023

Good Content and Assignments. Learned A lot.

By Pavlo G

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Aug 9, 2024

Great visual representation of the content!

By metin e

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Aug 2, 2024

it is well organized and presented course.

By Aditya l

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Jun 29, 2024

geed course but sometime felt so alienated

By jeff

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Jun 26, 2023

Thanks for this wonderful education course

By Kirtikumar P

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May 1, 2023

Awesome course. I really enjoyed it a lot.

By Martin

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Jul 5, 2023

Very interesting and informative course!

By Md S I

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Apr 26, 2023

Good course and Excellent InsInstructor.

By Aun K

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Mar 16, 2023

Great experience and a fantastic journey

By Partha R

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Feb 17, 2025

Solid class, probably the best of the 3

By Olusegun E

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Feb 5, 2025

Beautifully crafted course curriculum!

By Abderrahmene M

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Nov 11, 2024

The best course in the specialization

By DuNo

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Mar 21, 2024

amzing course and easy to understand

By Ryan T

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Aug 7, 2023

Great course. Straight to the point.

By Muhammad A J A

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Jun 4, 2023

Simple and deep course, I love it :)