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Exploratory Data Analysis with Seaborn(으)로 돌아가기

Coursera Project Network의 Exploratory Data Analysis with Seaborn 학습자 리뷰 및 피드백

372개의 평가
62개의 리뷰

강좌 소개

Producing visualizations is an important first step in exploring and analyzing real-world data sets. As such, visualization is an indispensable method in any data scientist's toolbox. It is also a powerful tool to identify problems in analyses and for illustrating results.In this project-based course, we will employ the statistical data visualization library, Seaborn, to discover and explore the relationships in the Breast Cancer Wisconsin (Diagnostic) Data Set. We will cover key concepts in exploratory data analysis (EDA) using visualizations to identify and interpret inherent relationships in the data set, produce various chart types including histograms, violin plots, box plots, joint plots, pair grids, and heatmaps, customize plot aesthetics and apply faceting methods to visualize higher dimensional data. 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, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰


2020년 9월 7일

This project is great for people go want to advances her career exploring new viz techniques. The instructor is great, clear and easy to follow. I will definitely recommend to take this project.


2020년 10월 3일

As a beginner, this was a very good insight into EDA for me. You will however, have to read the documentation and more articles to go in-depth. However, this is a very good introductory course.

필터링 기준:

Exploratory Data Analysis with Seaborn의 62개 리뷰 중 51~62

교육 기관: Johan R

2021년 4월 29일

I think it would be nice if I could play the video while using jupyter on my computer, it was a bit annoying to use the virtual machine, since if it was not on the page the video stopped

교육 기관: Rui L

2020년 5월 19일

A good tutorial for starters in Data Science. All knowledge taught in it is some basic.

교육 기관: Vishnu N S

2020년 12월 9일

GOOD start.. more api could be added

교육 기관: Anil S

2020년 5월 30일

Good Course with clear instructions

교육 기관: Anirudha S

2021년 5월 23일

Thank you. It was great.

교육 기관: Raj v

2020년 7월 14일

Explanations could have been more detailed. Parameters should be explained.

교육 기관: Nikhil A

2020년 7월 3일

Should have used more plots only 5 were there,but it was good

교육 기관: Andrea C

2020년 11월 20일

Good course for beginners, not for intermediate learners

교육 기관: Amrendra P S

2020년 8월 30일

Didn't learn much in this course. Just write the same code as explained in the videos and also the Instructor was not explaining thing in deep. This course I found worthless. It will be better if I had done some other courses rather than devoting my time for this

교육 기관: Linyu W

2020년 8월 10일

Not specific or even systematic. There're supposed to be more function in seaborn usefel for EDA

교육 기관: Alireza R

2021년 4월 17일

Very basic!

교육 기관: Fuat A

2020년 6월 1일

Not worth the money.