Goto

Collaborating Authors

Making MySQL 5,888 times faster

@machinelearnbot

When Jeff our architect first ran the benchmark I could not believe it! I was sitting in front of the terminal screen trying to take in what I had just seen. "Jeff is this correct?!" I asked. I had patiently waited 588 seconds (close to 10 minutes) for MySQL to execute a query and then watched as BigObject cranked out the same query in 0.1 seconds! That's a 5,888x boost in performance!


The Dark Side of Big Data

@machinelearnbot

Ashley Madison, IRS, Target, Sony…What do they have in common? Here we only name a few but of the most tremendous crisis of data breach in recent years - yes, it is happening and it is happening everywhere. The cost of data breach comes to a new high at 154 per record of stolen or leaked data, adding up to millions of data for each incident, including the law suits, losing customers and intangible assets of the companies. Big data, indeed, is turning the most valuable asset nowadays and that of course becomes a target of hackers and insider criminals. Among all the companies that suffer from data loss, financial services and healthcare are the most at stake with no doubt, for their data is the easiest to monetize.


Use H2O and data.table to build models on large data sets in R

#artificialintelligence

Last week, I wrote an introductory article on the package data.table. It was intended to provide you a head start and become familiar with its unique and short syntax. The next obvious step is to focus on modeling, which we will do in this post today. Atleast, I used to think of myself as a crippled R user when faced with large data sets. I would like to thank Matt Dowle again for this accomplishment. Algorithms like random forest (ntrees 1000) takes forever to run on my data set with 800,000 rows. I'm sure there are many R users who are trapped in a similar situation. To overcome this painstaking hurdle, I decided to write this post which demonstrates using the two most powerful packages i.e.


Big Data, IoT, Wearables: A Connected World with Intelligence

@machinelearnbot

At the CES 2015, I was fascinated by all sorts of possible applications of IoT – socks with sensors, mattresses with sensors, smart watches, smart everything – it seems like a scene in sci-fi movies has just come true. People are eager to learn more about what's happening around them and now they can. While I was at there I attended a talk given by David Pogue – he is awesome. He pointed out that the prevalence of smartphone is the key to the realization of the phenomenon called "Quantified Self." Smart phones play a vital role as a hub where all our personal data converge and present, seamlessly.


Big Data, IoT, Wearables: A Connected World with Intelligence

@machinelearnbot

At the CES 2015, I was fascinated by all sorts of possible applications of IoT – socks with sensors, mattresses with sensors, smart watches, smart everything – it seems like a scene in sci-fi movies has just come true. People are eager to learn more about what's happening around them and now they can. While I was at there I attended a talk given by David Pogue – he is awesome. He pointed out that the prevalence of smartphone is the key to the realization of the phenomenon called "Quantified Self." Smart phones play a vital role as a hub where all our personal data converge and present, seamlessly.