Exploratory Data Analysis with Seaborn
12,616명이 이미 등록했습니다.
12,616명이 이미 등록했습니다.
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.
Data Visualization (DataViz)
작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.
작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.
분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.
SP 제공2020년 6월 25일
This was my first guided project . It was a nice experience and the course material was truly helpful for me. The instructor's pace of teaching was absolutely stunning.
PG 제공2020년 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.
JR 제공2021년 4월 28일
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
HA 제공2020년 6월 29일
The course is a great course for a data scientist! Very practical and I like the way the instructor explains the concept and the interpretation of the data.