Chevron Left
Zurück zu Exploratory Data Analysis with Seaborn

Bewertung und Feedback des Lernenden für Exploratory Data Analysis with Seaborn von Coursera Project Network

402 Bewertungen

Über den Kurs

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....



7. Sep. 2020

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.


3. Okt. 2020

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.

Filtern nach:

1 - 25 von 67 Bewertungen für Exploratory Data Analysis with Seaborn

von Ravi K

21. Apr. 2020

von Rob O

23. Apr. 2020

von Anees A

3. Mai 2020

von Suhaimi C

18. Nov. 2020

von Pavithra K

1. Aug. 2020

von Abhijit T

9. Apr. 2020


3. Mai 2020

von Ujjwal K

10. Mai 2020

von Punam P

15. Mai 2020

von Mukund P

13. Mai 2020

von Rishabh R

17. Mai 2020

von Dr M M S

8. Nov. 2020

von Shri H

7. Nov. 2020

von Nesmary G M D

14. Mai 2022


12. Juni 2020

von Hector P

7. Sep. 2020

von Pawan K G

4. Okt. 2020

von Sayak P

26. Juni 2020

von Asmae A

10. Apr. 2022

von HAY a

29. Juni 2020

von Aditya T

5. Nov. 2020

von Gourav K

27. Juli 2020

von Srikanth C

16. Juni 2020

von Carlos O G M

1. Nov. 2022

von omkar

10. Juni 2020