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Volver a Mathematics for Machine Learning: PCA

Opiniones y comentarios de aprendices correspondientes a Mathematics for Machine Learning: PCA por parte de Imperial College London

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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....

Principales reseñas


6 de jul. de 2021

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.


16 de jul. de 2018

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.

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451 - 475 de 716 revisiones para Mathematics for Machine Learning: PCA

por Shraavan S

4 de mar. de 2019

Programming assignments are a little difficult. Background knowledge of Python is recommended for this course.

por Andrew D

2 de jun. de 2019

Very difficult course, make sure to do the prereq courses first and understand everything from those courses.

por Neelam U

23 de sep. de 2020

The programming assignments were quite challenging. Some part of the course can discuss this aspect as well.

por Paulo N A J

18 de ago. de 2020

It is a good course with hard programming, but the assignments could be improved. The forum helps a lot.

por Ibon U E

7 de ene. de 2020

The derivations of some concepts have been more vague compared to other courses in this specialization.

por Max W

19 de abr. de 2020

Very challenging, could have used a few more videos to really explain or give a few more examples

por Abhishek T

12 de abr. de 2020

The structure could have been better. Some of the weeks were too crowded as compared to others

por Phuong A N

7 de ago. de 2020

very difficult course. But I hope that it will be useful fore my machine learning studying

por kerryliu

30 de jul. de 2018

still have room for improvement since lots of stuffs can be discussed more in detail.

por Ruan V S

13 de oct. de 2019

Harder than expected, the content is good and is well worth the struggle!

por Xin W

6 de sep. de 2019

This course is full of mathematical derivation, so it is kind of boring.

por Bintang K P P

26 de mar. de 2021

We need more basic example and exercise before taking graded assignment

por Felipe T B

10 de ago. de 2020

Computational exercises could have more support from the professors.

por Jiaxuan L

15 de jul. de 2019

Overall a good course. Very limited introduction to Python though.

por Chow K M

28 de jul. de 2020

Quite challenging. Need to keep notes for programming assignment.

por Lafite

4 de feb. de 2019


por Attili S

19 de ago. de 2020

Great course! It could have elaborated more in the week 4 PCA

por Chenyu W

24 de jul. de 2021

feels like it progresses too fast. otherwise great content

por Ashok B B

6 de feb. de 2020

Course was challenging , but learned the maths behind PCA,

por Cesar A P C J

23 de dic. de 2018

Good content, just need to fix the assignments' platform.

por Mohamed F

30 de sep. de 2022

Excellent course, but the last assignment wasn't obvious

por Dave D

30 de may. de 2020

This course was a fair overview of a very complex topic.


13 de may. de 2020

It is very informative and hands-on based Course for PCA

por Saiful B I

4 de may. de 2020

Not as good as the other two courses..but interesting!

por Sharon P

24 de sep. de 2018

Mathematically challenging, but satisfying in the end.