I’ve previously written a lot on data mining in the abstract; now, I want to start taking you through some practical applications. Welcome to the fascinating world of the recommendation engine- this post will walk through the concepts, and later posts will teach you how to implement your own. What
In a first, the White House has appointed a certain Dr. D.J. Patil as the Deputy Chief Technology Officer for Data Policy and Chief Data Scientist, it was announced Wednesday. Dr. Patil will report to erstwhile Google executive Megan Smith, who is now the U.S.’ Chief Technology Officer. “As part
TOP DATACONOMY ARTICLES 8 Trends In Big Data For 2015 “As a Big Data recruiter, the speed of change in the industry never ceases to amaze me. I can’t fail to get up in the morning and wonder what the next year (or day) might bring in this ever changing
The list for 25 Hottest Skills of 2014 that got people hired according to the business networking service provider, LinkedIn, came out mid-December last year, and there has been a significant shuffling since 2013. What came out on top as the number one on this list was Statistical Analysis and
TOP DATACONOMY ARTICLES Python Packages For Data Mining “Just because you have a “hammer”, doesn’t mean that every problem you come across will be a “nail”.The intelligent key thing is when you use the same hammer to solve what ever problem you came across. Like the same way when we
With the advent of Big Data and the rapidly growing scale of web-applications, monolithic relational databases were replaced by scalable, partitioned, NoSQL databases and HDFS; individual queries to relational databases were replaced by the likes of Hive and Pig. This growing scale and partitioned consumption model brought about by these
“The biggest issue for governments today is how to be relevant. If all citizens are treated with dignity and invited to collaborate, it can be easier for administrations to have a direct finger on the pulse of the nation rather than lose it in transmission through multiple layers of bureaucracy”.
Ferris is a full stack data scientist who enjoys building products at the forefront of intelligent technology. He understands that the next generation won’t be concerned with how to use technology to do things, but will expect technology to do and adapt for them. See all of Ferris’ posts here.
“Where there is data smoke, there is business fire.” – Thomas Redman The idea of Data Smoke is quite a brilliant analogy by Thomas Redman. It adequately explains why so much emphasis has been placed on tools, personnel, and culture within companies over the past decade. To understand the quote, however, it’s
LinkedIn, the social networking company with one of the world’s first pioneering data science teams, has split its crew to be placed under different departments. The data science team which had worked in the product division, had consisted of two branches through the years – the product data science team,