Tips for getting started on Kaggle (datamining)

November 30, 2011
By

(This article was first published on Doodling with Data, and kindly contributed to R-bloggers)

Ever since I heard about Kaggle.com at this year's Bay Area Data Mining Camp, I've wanted to participate. But I was feeling somewhat intimidated.
Jeremy Howard's "Intro to Kaggle" talk at yesterday's MeetUp (DataMining for a Cause) was exactly what I needed.
He had a number of tips for beginners. His was exactly the talk that I was looking for, though I didn't know it. I am sharing some of his tips here, in case it helps others as well.

Jeremy Howard's Tips for Getting Started on Data Mining competitions at Kaggle

* Visit the Kaggle site and spend at least 30 minutes every day hanging around. Read the forum, the competition pages, and read the Kaggle blog
* It is much better to start participating in competitions which are just starting up, rather than in ones where there are 100s of entries and teams already well on their way
* Aim to make at least one submission each and every day
* Jeremy himself participates in competitions to see where he stands, and to learn and get better
* He'd start out making trivial submissions (all zero's, or alternate zero's, all entries as averages) until his algorithm got better
* A lot of people who compete use R (and SAS, Excel or Python)
* Nearly 50% of the winning entries use Random Forest techniques.
* If you place in the top 3, that is great. But personal improvement and learning should be the goal.
* As you get better, you might get invited to "private competitions."
* Every day, strive to do a little better and improve your submission's performance, scoring and ranking

Related Links:

To leave a comment for the author, please follow the link and comment on his blog: Doodling with Data.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: 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.