Chevron Left
Back to Principal Component Analysis with NumPy

Learner Reviews & Feedback for Principal Component Analysis with NumPy by Coursera Project Network

4.6
stars
293 ratings

About the Course

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....

Top reviews

TS

Oct 4, 2020

V

e

r

y

g

o

o

d

G

u

i

d

e

d

e

p

r

o

j

e

c

t

TA

Oct 30, 2020

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

Filter by:

26 - 50 of 50 Reviews for Principal Component Analysis with NumPy

By rishabh m t

•

Sep 25, 2020

highly informative

By Gangone R

•

Jul 3, 2020

very useful course

By Kamol D D

•

Apr 18, 2020

Very Satisfactory

By Hari O U

•

Apr 19, 2020

Great experience

By ELANGOVAN K

•

Jul 21, 2020

Good project

By ARUNAVA B

•

Aug 13, 2020

excellent.

By SASI V T

•

Jul 12, 2020

EXCELLENT

By Abhishek P G

•

Jun 15, 2020

satisfied

By Kamlesh C

•

Jul 7, 2020

Thanks

By Raja R G K

•

Aug 24, 2020

great

By BRIJESH S

•

Feb 23, 2023

Good

By p s

•

Jun 29, 2020

Good

By tale p

•

Jun 28, 2020

good

By Vajinepalli s s

•

Jun 16, 2020

nice

By Carlos C

•

Dec 14, 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.

By Vipul P

•

Jun 14, 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.

By prashant p

•

Jun 1, 2020

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

By Alok a

•

Aug 5, 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.

By Sumit S

•

May 31, 2020

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

By Ashutosh S T

•

May 9, 2020

Excellence experiece, good content for begineers, thanx coursera.

By GUNDA N

•

May 10, 2020

The instructor was good with explanation .

By Yogeshwari

•

Oct 2, 2020

Very Good explained project

By Kumar S

•

May 17, 2023

No in-depth explanations. The guy was just throwing around linear algebra jargons. Maybe he himself did not understand what they actually mean and why are they relevant here. Just a code copy paste course

By Задойный А

•

Jul 24, 2020

Очень слабые объяснения. Всё как "магия".