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Mathematics for Machine Learning: PCA に戻る

インペリアル・カレッジ・ロンドン(Imperial College London) による Mathematics for Machine Learning: PCA の受講者のレビューおよびフィードバック

4.0
2,836件の評価

コースについて

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction. At the end of this course, you'll be familiar with important mathematical concepts and you can implement PCA all by yourself. If you’re struggling, you'll find a set of jupyter notebooks that will allow you to explore properties of the techniques and walk you through what you need to do to get on track. If you are already an expert, this course may refresh some of your knowledge. The lectures, examples and exercises require: 1. Some ability of abstract thinking 2. Good background in linear algebra (e.g., matrix and vector algebra, linear independence, basis) 3. Basic background in multivariate calculus (e.g., partial derivatives, basic optimization) 4. Basic knowledge in python programming and numpy Disclaimer: This course is substantially more abstract and requires more programming than the other two courses of the specialization. However, this type of abstract thinking, algebraic manipulation and programming is necessary if you want to understand and develop machine learning algorithms....

人気のレビュー

WS

2021年7月6日

Now i feel confident about pursuing machine learning courses in the future as I have learned most of the mathematics which will be helpful in building the base for machine learning, data science.

JS

2018年7月16日

This is one hell of an inspiring course that demystified the difficult concepts and math behind PCA. Excellent instructors in imparting the these knowledge with easy-to-understand illustrations.

フィルター:

Mathematics for Machine Learning: PCA: 201 - 225 / 706 レビュー

by Dora J

2019年2月3日

Great course including many useful refreshers on foundational concepts like inner products, projections, Lagrangian etc.

by Trung T V

2019年9月18日

This course is very helpful for me to understand Math for ML. Thank you Professors at Imperial College London so much!

by Mukund M

2020年5月24日

Professor Deisenroth is amazing. Very tough course but appreciated all the derivations and explanations of concepts.

by David H

2019年3月21日

It was challenging but worth it to enhance the mathematic skills for machine learning. Thanks for the awesome course.

by Lee F

2018年9月28日

This was the toughest of the three modules. It gave me a strong foundation to continue pusrsuing machine learning.

by Nileshkumar R P

2020年5月6日

This course was tough but awesome. Lots of things i learnt from this course. Great course indeed and worth doing.

by Carlos J B A

2021年5月17日

Undoubtedly one of the best courses I have taken on mathematics for Machine Learning with world-class teachers.

by Kuntal T

2021年2月15日

one of the best course to learn whats happening in machine learning and how it make sense through mathematics.

by 037 N S

2020年7月30日

The PCA part Was a bit tricky barely handle the concepts.

thank you imperial team for such interactive course

by Krzysztof

2019年8月21日

One of the most challenging course in my life - almost impossible without python and mathematics background.

by Javier d V

2021年6月25日

Great course. An intermediate mathematical background is requiered. This is a strength in terms of learning

by Pratama A A

2020年8月25日

Need more Effort to grasp the materials explained_-" you need to be patience,the lecturer is really on top

by Nelson S S

2020年7月29日

Excellent course ... Quite challenging, a little difficult but I have learned a lot ... Thank you ...

by sameen n

2019年9月6日

Amazing course and provides basic introduction for the PCA. Need for programming help in this course.

by Brian H

2020年2月24日

Great course. I appreciate the rigor and clear mathematical explanations provided by Dr. Deisenroth.

by Natalya T

2019年2月25日

exellent course! nice python wokring enviroment and very good explanation at each topic. thank you!

by Aishik R

2020年1月18日

Excellent and to-the-point explanations, useful assignments to make the concepts etched in memory

by Haoquan F

2022年2月13日

It's overall wonderful but the week 4's programming assignment really struggled and confused me.

by KAMASANI V R

2020年6月20日

This course helped me in getting a deeper knowledge on Principal Component Analysis. Thank You.

by Wei X

2018年10月16日

concise and to the point. Might want to introduce a bit the technique of Lagrangin multiplier

by Fab V

2022年7月31日

A fascinating course letting people explore the beauties of Mathematics and Machine Learning

by Leonardo H T S

2021年5月2日

This was an amazing course, I really enjoyed it and learn a lot!

Thank you so much, greetings

by Wahyu N A M

2021年3月27日

I'm struggle with assigments of week 4 about implementing PCA. But, yeaah finally i got this

by Mayank

2020年12月3日

This course cleared so many concepts and enabled me to further master the subject on my own.

by Ripple S

2020年3月17日

I learnt a lot from this course and now I think I am much more familiar with this algorithm.