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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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702 reseña

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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

WS

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.

JS

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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626 - 650 de 700 revisiones para Mathematics for Machine Learning: PCA

por vignesh n

12 de sep. de 2018

Explaination of many things are skipped, assumption was made by the instructor that lot of things were already known by the learner. It could have been much better.

por Maksim S

25 de mar. de 2020

The difficulty of the course is inadequate and the pace is not balanced. Requires a lot of search for additional resources to understand materials. I cancelled.

por Ghanem A

20 de jul. de 2021

Response to questions is very slow. Support to learners is not sufficient

Programming assignments are not explained well (some I believe have errors)

por Kovendhan V

11 de jul. de 2020

After first two amazing courses in this specialisation, third course was a huge let down. One skill I learnt from this last course is patience.

por Martin H

8 de dic. de 2019

Lack of examples to clarify abstract concepts. Big contrast in quality compared to the other courses in this specialization.

por Jamiul H D

7 de ago. de 2020

Poor explanation by the instructor. Previous ones were very helpful. I didn't understand many topics well

por Lavanith T

21 de ago. de 2020

Everything is okay but there is a huge drawback with the programming explanation part.

por Xiao L

3 de jun. de 2019

very wired assignment, a lot of error in template code. The concept is not clear.

por Sai M B

3 de ago. de 2020

The lectures were not clear. I had to use other sources to understand lectures.

por Pawan K S

20 de jun. de 2020

This course was the hardest I encountered in this specialisation.

por Mohamed A H

18 de ago. de 2021

it was not clear alot of the time and it was really hard

por Kirill T

26 de jul. de 2020

Way worse than the previous courses. Lacks explanations

por Kevin O

27 de mar. de 2021

Really interesting topic but not nearly enough detail.

por Amr F M R

22 de sep. de 2020

I think course material was not explained well at all.

por Timothy M

22 de abr. de 2021

The lectures and assignments did not synergize well.

por Aravindan B

23 de sep. de 2019

Need to improve the content and delivery of content.

por Mohammed A A

19 de jul. de 2020

the course is too shallow with difficult code exame

por Scoodood C

28 de jul. de 2018

Video lecture not as intuitive as previous courses.

por Michael B

21 de nov. de 2019

Programming assignments not well explained

por youssef s

27 de jul. de 2020

very poor explanation of things

por Murilo F S

24 de ene. de 2021

not good teacher :Z

por Salah E

4 de ago. de 2020

again too hard

por Alan

4 de ago. de 2020

Very disappointing compared to the other courses. Recommend a complete revision of the course materials. Quizzes often had nothing to do with the preceding video. I worked through a week two quiz using the extensive notes in the discussion forum and by searching the internet. The next lecture proceeded in the same vein: the instructor failed to cover the material in video leaving me to figure out what the material was and then figure out how to find that material on the internet or in reference books. At that point, it just was not worth the time to take the course.

por 周玮晨

8 de jun. de 2018

This course is far far far behind my expectations.The other two course in the specializition is fantastic. There is no visualization in this course, Instructor is always doing his algebra, concepts are poorly explained. I can't understand a lot of concepts in this course because of my poor math background.But why do i take ths course if i have a solid background in math? Programming assignments is not difficult but hard to complete because of vaguely clarification.Plenty of time wasted to find what should i do, its' really frustrating.

por Hannah Q

26 de abr. de 2021

This is the worst course among 3 courses in this math for machine learning specialization, but this is also the most important one as it comprises the other 2 courses. the homework is not well designed, the lecture is not taught enough to finish the homework. the last coding assignment has so many errors. and TA is never available, there are just a group of people tried really hard to help each other in the discussion forum, and please read the discussion forum every one is confused and suffering from your this bad course.