Category Archives: Kaggle

Big Data Quotes of the Week

“These new technologies and approaches have done much more than just solve the problems around petabytes of data and thousands of events per second. They are the right way to do data. That’s why I’m not convinced the term ‘big … Continue reading

Posted in Big Data Analytics, Big Data Futures, Kaggle, MapR, Microsoft, NASA | Leave a comment

Revisiting Big Data and Crowdsourcing: Kaggle Today

I launched this blog a year ago in June 2011. In one of my first posts, I discussed “Crowdsourcing and Big Data,” offering a typology of crowdsourcing and connecting it to big data by mentioning a little-known (at the time) … Continue reading

Posted in Big Data Analytics, Competitions, Crowdsourcing, Kaggle, Predictive analytics | Leave a comment

Top Ten Kaggle Data Scientists

1. Alexander D’yakonov An academic in the Faculty of Computational Mathematics and Cybernetics department at Moscow State University, Alexander modestly describes his favorite problem-solving technique as “luck.” Despite this, the 33-year-old Russian has earned a reputation for using methods known … Continue reading

Posted in Data Scientists, Kaggle | 1 Comment

Domain Expertise vs. Machine Learning: The Debate Continues

By starting to rank all the data scientists participating in its competitions, Kaggle today advanced further its argument that data science is a generic set of skills that can be applied to any problem without prior domain expertise. Talking to … Continue reading

Posted in Competitions, Data Scientists, Domain Expertise, Kaggle, Machine Learning, Skills | Leave a comment

Data Scientist: 6 Definitions

From Simon Rogers, “What is a Data Scientist?”: “Someone who can bridge the raw data and the analysis – and make it accessible. It’s a democratising role; by bringing the data to the people, you make the world just a … Continue reading

Posted in, Data Science, Data Scientists, Kaggle, LinkedIn | 2 Comments

Crowdsourcing and Big Data

The Wikipedia article on Big Data says it “requires exceptional technologies to efficiently process large quantities of data within tolerable elapsed times.” The examples given (Hadoop, MapReduce, Cloud Computing, etc.) do not include one very exceptional technology, the human brain, … Continue reading

Posted in Appswell, Business Impact, Crowdsourcing, Data Scientists, Innocentive, Kaggle, uTest | 8 Comments