# 學生對 伦敦帝国学院 提供的 Mathematics for Machine Learning: PCA 的評價和反饋

4.0
2,600 個評分
645 條評論

## 課程概述

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....

## 熱門審閱

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.

NS
2020年6月18日

Relatively tougher than previous two courses in the specialization. I'd suggest giving more time and being patient in pursuit of completing this course and understanding the concepts involved.

## 176 - Mathematics for Machine Learning: PCA 的 200 個評論（共 641 個）

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.

2021年5月17日

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

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.

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

2019年8月21日

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

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

2020年7月29日

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

2019年9月6日

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

2020年2月24日

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

2019年2月25日

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

2020年1月18日

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

2020年6月20日

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

2018年10月16日

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

2021年5月2日

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

Thank you so much, greetings

2021年3月27日

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

2020年12月3日

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

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.

2020年4月22日

extremely informative and really help me understand the basic math in Machine learning

2020年4月17日

Course was challenging, so does the math. It was a very excellent learning experience!

2019年11月14日

This course is also so helpful, and the lecturer is so predominant on what he taught.

2019年10月20日

Truly hardcore course if your are a noob in reduced order modelling. Very challenging

2020年8月8日

Algebra, Calculus and PCA

These are all excellent, if you have mathematics knowledge

2019年11月5日

Excellent course and extremely difficult one to grasp at one go. Regards Arijit Bose

2018年5月25日

Very hard to follow, but you need to do it to understand machine learning very well.

2019年7月27日

I have thoroughly enjoyed every course of this specialization. Thank you very much.