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学生对 Coursera Project Network 提供的 Data Analytics: Scraping Data using Hadley Wickam's Rvest package in R 的评价和反馈

4.2
39 个评分
10 条评论

课程概述

In this 1-hour long project-based course, you will learn how to (complete a training and test set using an R function, practice looking at data distribution using R and ggplot2, Apply a Random Forest model to the data using the FFTrees package in R, and examine the results using a Confusion Matrix. Note: 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....

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VP
Jun 21, 2020

Thank you so much for this project. It was really helpful. The style of teaching is 10/10.\n\nLooking forward to the next session.

PN
Aug 22, 2020

Very useful and easy to understand project.Thank you

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1 - Data Analytics: Scraping Data using Hadley Wickam's Rvest package in R 的 10 个评论(共 10 个)

创建者 Vikash P

Jun 22, 2020

Thank you so much for this project. It was really helpful. The style of teaching is 10/10.

Looking forward to the next session.

创建者 Phuong A N

Aug 23, 2020

Very useful and easy to understand project.Thank you

创建者 Abdullah B H

Jul 15, 2020

Everything was great....new experience!

创建者 Cherry I T

Jul 5, 2020

you must learn

创建者 Raisa N E

Nov 18, 2020

good!

创建者 p s

Jun 26, 2020

Good

创建者 tale p

Jun 24, 2020

good

创建者 Max

Sep 16, 2020

"practice looking at data distribution using R and ggplot2,

Apply a Random Forest model to the data using the FFTrees package in R, and examine the results using a Confusion Matrix."

Where is that in the course? I just saw an overview and some practice with Rvest package, but beyond that there was no RF, ggplot2 nor confusion matrix.

创建者 Mayank A

Jun 24, 2020

It was a very quick overview of how to scrape the data. The instructor could have saved an R script on the desktop for learner's quick access.

创建者 Paolo O

Oct 30, 2020

I found it a loss of time and bit frustrating. What it takes 2 hours here (and more to figure out what's not working if you run on a different R version) it can be better achieved with a few minutes of good reading. No concepts explained!