Chevron Left
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

4.5
stars
1,293 ratings

About the Course

Newly updated for 2024! After completing this course, learners will be able to: • Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc. • Apply common vector and matrix algebra operations like dot product, inverse, and determinants • Express certain types of matrix operations as linear transformations • Apply concepts of eigenvalues and eigenvectors to machine learning problems Mathematics for Machine Learning and Data science is a foundational online program created in by DeepLearning.AI and taught by Luis Serrano. This beginner-friendly program is where you’ll master the fundamental mathematics toolkit of machine learning. 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 plugins and visualizations to help you see how the math behind machine learning actually works. Upon completion, you’ll understand the mathematics behind all the most common algorithms and data analysis techniques — plus the know-how to incorporate them into your machine learning career. This is a beginner-friendly program, with a recommended background of at least high school mathematics (functions, basic algebra). We also recommend a basic familiarity with Python (loops, functions, if/else statements, lists/dictionaries, importing libraries), as labs use Python and Jupyter Notebooks to demonstrate learning objectives in the environment where they’re most applicable to machine learning and data science. If you are already familiar with the concepts of linear algebra, Course 1 will provide a good review, or you can choose to take Course 2: Calculus for Machine Learning and Data Science and Course 3: Probability and Statistics for Machine Learning and Data Science, of this specialization....

Top reviews

NA

Jun 17, 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 26, 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.

Filter by:

201 - 225 of 351 Reviews for Linear Algebra for Machine Learning and Data Science

By Tuhin D

•

May 23, 2023

Very intuitive!

By Dr.V.Parimala

•

Apr 10, 2023

good experience

By Parampreet S

•

Jun 26, 2023

Great Course!

By MARC F

•

Apr 11, 2023

Great course!

By Sabeur M

•

Jan 15, 2024

Great cours

By MUHAMMAD A

•

Jul 26, 2023

Its awesome

By Ariana H

•

Jun 4, 2023

I loved it.

By Behzad N

•

Nov 5, 2023

Fantastic!

By Rajarshi M

•

Aug 23, 2023

Excellent!

By adeel s

•

Jul 26, 2023

excellent

By Muhammad K M

•

Mar 20, 2024

excelent

By Dwiki H

•

Sep 29, 2023

so great

By khushilal s

•

Sep 4, 2023

All good

By ARON H T

•

Mar 13, 2023

Awesome!

By Muhammad K I

•

Mar 23, 2024

awesome

By moustafa e

•

Apr 20, 2023

amazing

By Polina K

•

Feb 14, 2024

Great!

By Susi S M

•

Mar 21, 2024

Great

By Ramy I A

•

Mar 7, 2024

thanx

By Michael C

•

Dec 19, 2023

Great

By Stephen C

•

Dec 9, 2023

10/10

By RIPALDO L B

•

Sep 27, 2023

Keren

By Shahid R

•

Jun 27, 2023

great

By Anggi P S

•

Mar 23, 2024

good

By Syehan H S

•

Oct 17, 2023

good