Mathematics for Machine Learning: Linear Algebra(으)로 돌아가기

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In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.
Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before.
At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

Dec 23, 2018

Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.

Apr 01, 2018

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.

필터링 기준:

교육 기관: Sameen N

•Feb 22, 2019

It give me basic understanding of vectors and matrices. Understand the concepts of eigen values and eigen vectors and got understanding of how google pagerank works.

교육 기관: Tichakunda

•Jan 03, 2019

This is a top intro class and looks at linear algebra from first principles , focusing on the intuition (and the math follows very smoothly). Perfect class, really!

교육 기관: Jaffer K

•Sep 18, 2018

A really good refresher of past concepts. It builds intuition into basics that bug many people. This course can help anyone build a good foundation in Linear Algebra

교육 기관: MohAmedd M

•Jul 31, 2018

Excellent foundation course , gave me an idea how linear algebra being used for algorithms developing and enhance my intuitive about solving linear algebra problems

교육 기관: Alphanso W

•Dec 22, 2019

Truly a wonderful course. I wish you could have touched on the interpretation of determinants a bit more. Especially since strong knowledge of it is needed in PCA.

교육 기관: Benedict N Y E

•Sep 01, 2019

Loved the course. The codes were quite hard to understand but I managed to understand it after a some hard work. Overall good experience. Highly recommend for all.

교육 기관: Eric P

•Mar 19, 2019

I really liked the pace of this course. Not too fast, not too slow. I also enjoyed the focus on intuitive understandings and linear algebra in the context of ML.

교육 기관: Joshua S

•Apr 21, 2018

Great introduction to linear Algebra! Wish my college experience was this good! I highly recommend an iPad Pro and Apple pencil to take notes. Man this is awesome.

교육 기관: Xiangxin S

•May 29, 2018

great class, only focused on the core concepts of linear algebra, and try to build a intuition of how these concepts fit in later on machine learning applications

교육 기관: muhammad r k k

•Jun 28, 2019

you must do this course...the best course to learn mathematics behind machine learning. Look no further.This is an amazing million dollar course for data science

교육 기관: KANHAIYA K

•Jul 21, 2019

Easy to get the concepts of Vectors, Eigen Values, Eigen Vectors, and Page Rank algorithm. I can now implement some algorithms which needs matrix manipulations.

교육 기관: Kamil G

•Jul 11, 2018

Great content, clarity and visualisations. I found this course extremely useful, it gives me fundamentals to understand more advanced machine learning problems.

교육 기관: Edwin G P P

•Sep 01, 2019

El curso desarrolla varias herramientas importantes para el manejo de vectores y matrices enfocadas en aplicaciones de Machine Learning. Es bastante intuitivo.

교육 기관: aman

•Aug 18, 2018

This course is a must for all the people who wants to go deep into machine learning and data science as this covers the prerequisites of the courses available.

교육 기관: Rambabu Y

•Jul 28, 2018

It is highly recommended. Very useful to those who are interested in AI and ML and looking for deep dive. Thanks very much coursera and imperial college London

교육 기관: V A R

•Jun 15, 2019

Brilliant course, thought intuitively and had a significant impact on my perspective in viewing transformation and other operations related to linear algebra.

교육 기관: Zvinodashe M

•Jul 26, 2018

Excellent course a little challenging but just the right pace and depth to get one back up to speed with linear algebra, looking to build from this foundation

교육 기관: Kyle W

•Dec 06, 2018

Excellent course. It's very practical - focuses on building your intuition of core concepts and applying those concepts through simple programming exercises.

교육 기관: Anastasios P

•Dec 22, 2019

Great course to get introductory knowledge and good foundation on linear algebra, especially Eigenvalues and Eigenvectors and some basic python programming.

교육 기관: Xiran L

•Jul 30, 2019

This course is amazing. Week 5 quiz is tricky but all the others are fine. The course might take longer than expected to complete but it's totally worth it.

교육 기관: Sujeet B

•Jun 19, 2019

Very good; contents covered gives an intuition of what's happening beneath the Mathematics. The lectures are interactive (which keeps your brain working).

교육 기관: GUO J

•Nov 05, 2019

The programming assignments are very well-designed. They are easily to follow and give me confidence to use Python deal with complex mathematic problems.

교육 기관: Serge H k

•Nov 25, 2018

I love the stuff that I learned: the usefulness of eigenvalues and eigenvectors, coding pagerank algorithm, gram Schmidt to create orthonormal basis, ...

교육 기관: Lee F

•Sep 07, 2018

Enjoyed the course a lot! It stretched me at times, and I definitely got what I needed and know where to go to fill in any knowledge gaps in the future.

교육 기관: SANDEEP K D

•Nov 09, 2019

A new way of looking at eigen values and vectors, every engineer should do this course.

It will help developing strong fundamentals for machine learning.

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