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Вернуться к Principal Component Analysis with NumPy

Отзывы учащихся о курсе Principal Component Analysis with NumPy от партнера Coursera Project Network

Оценки: 280
Рецензии: 47

О курсе

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....

Лучшие рецензии


4 окт. 2020 г.



30 окт. 2020 г.

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

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26–47 из 47 отзывов о курсе Principal Component Analysis with NumPy

автор: Hari O U

19 апр. 2020 г.

Great experience


21 июля 2020 г.

Good project

автор: ARUNAVA B

13 авг. 2020 г.


автор: SASI V T

12 июля 2020 г.


автор: Abhishek P G

15 июня 2020 г.


автор: Kamlesh C

7 июля 2020 г.


автор: Raja R G K

24 авг. 2020 г.


автор: p s

29 июня 2020 г.


автор: tale p

28 июня 2020 г.


автор: Vajinepalli s s

16 июня 2020 г.


автор: Carlos C

14 дек. 2020 г.

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.

автор: Vipul P

14 июня 2020 г.

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.

автор: prashant p

1 июня 2020 г.

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

автор: Alok a

5 авг. 2020 г.

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

автор: Sumit S

31 мая 2020 г.

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

автор: Ashutosh S T

9 мая 2020 г.

Excellence experiece, good content for begineers, thanx coursera.

автор: GUNDA N

10 мая 2020 г.

The instructor was good with explanation .

автор: Baviskar Y S

2 окт. 2020 г.

Very Good explained project

автор: Jorge G

25 февр. 2021 г.

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.

автор: Mohinder S

3 июня 2020 г.

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

автор: Задойный А

24 июля 2020 г.

Очень слабые объяснения. Всё как "магия".