Free Kaggle Machine Learning Tutorial for R

July 13, 2016
By

(This article was first published on DataCamp Blog, and kindly contributed to R-bloggers)

Always wanted to compete in a Kaggle competition, but not sure you have the right skill set? We created a free interactive Machine Learning tutorial to help you out!Together with the team behind Kaggle, we have developed a free interactive tutorial on how to apply Machine Learning Techniques that can be used in your Kaggle competitions.  Step by step, through fun coding challenges, the tutorial will learn you how to predict survival rate for Kaggle’s Titanic competition using R and Machine Learning. Start the Machine Learning with R tutorial now!Kaggle TutorialThis free R tutorial is provided by DataCamp, an online interactive education platform that offers courses in data science and R programming. Each course is built around a certain data science topic, and combines video instruction with in-browser coding challenges so that you can learn by doing. You can start every course for free, whenever you want, wherever you want.

The Machine Learning Tutorial

In this Machine Learning tutorial, you will gradually learn how basic machine learning techniques can help you to make better predictions. Go through all the steps, upload your results to Kaggle, and see your ranking go up. No need to install anything. Everything will take place in the comfort of your own browser. Learn:

  • How to load and manipulate your data set using R.
  • Make basic predictions using variables such as age and gender.
  • How to create your first decision tree.
  • How to make use of feature engineering to improve results.
  • What exactly ‘overfitting’ means, and how to avoid it.
  • How to make use of the ML technique Random Forests.

So don’t wait and get started. Want to see other topics covered as well? Just let us know on Twitter.

To leave a comment for the author, please follow the link and comment on their blog: DataCamp Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)