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Comentários e feedback de alunos de Principal Component Analysis with NumPy da instituição Coursera Project Network

4.6
estrelas
282 classificações

Sobre o curso

Welcome to this 2 hour long project-based course on Principal Component Analysis with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to implement and apply PCA from scratch using NumPy in Python, conduct basic exploratory data analysis, and create simple data visualizations with Seaborn and Matplotlib. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, NumPy, and Seaborn pre-installed....

Melhores avaliações

TS

4 de out de 2020

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TA

30 de out de 2020

Good Introductory project to gain insights into PCA using Numpy and python.

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26 — 47 de 47 Avaliações para o Principal Component Analysis with NumPy

por Hari O U

19 de abr de 2020

Great experience

por ELANGOVAN K

21 de jul de 2020

Good project

por ARUNAVA B

13 de ago de 2020

excellent.

por SASI V T

12 de jul de 2020

EXCELLENT

por Abhishek P G

15 de jun de 2020

satisfied

por Kamlesh C

7 de jul de 2020

Thanks

por Raja R G K

24 de ago de 2020

great

por p s

29 de jun de 2020

Good

por tale p

28 de jun de 2020

good

por Vajinepalli s s

16 de jun de 2020

nice

por Carlos C

14 de dez de 2020

This is a great way of learn through hands-on activities. The only inconvenient was the slowly connection to the Coursera project platform. Sometimes I couldn't work at all for a long time because my pointer got freeze. The idea of learning with the help of an instructor is excellent but it just needs a better implementation.

por Vipul P

14 de jun de 2020

The course felt a bit too short and the time allotted for the guided project was barely enough to complete it in time leaving little to no room for thinking and rewinding the videos which made it a bit uncomfortable to take.

por prashant p

1 de jun de 2020

Course is amazing, got many concepts clear, learned a lot. Would also be great if more than one datasets are taken as excercise.

por Alok a

5 de ago de 2020

It's a good course for someone to try out his knowledge of the basic packages and the concepts and the maths behind PCA.

por Sumit S

31 de mai de 2020

It was quite conceptional but the instructor made it easy for me to implement and follow along.

por Ashutosh S T

9 de mai de 2020

Excellence experiece, good content for begineers, thanx coursera.

por GUNDA N

10 de mai de 2020

The instructor was good with explanation .

por Baviskar Y S

2 de out de 2020

Very Good explained project

por Jorge G

25 de fev de 2021

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.

por Mohinder S

3 de jun de 2020

Well, this project seems to be very basic and can be created using WEBSITE LIKE:

https://www.geeksforgeeks.org/principal-component-analysis-with-python/

por Задойный А

24 de jul de 2020

Очень слабые объяснения. Всё как "магия".