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Randomness is all around us. Its existence sends fear into the hearts of predictive analytics specialists everywhere -- if a process is truly random, then it is not predictable, in the analytic sense of that term. Randomness refers to the absence of patterns, order, coherence, and predictability in a system.
We all love features... lots of features! ...in our new cars, in our gadgets, in our smart phones, in our toys, and in our data sets!
Consider this toy that we found at the thrift store for under $6.00:
This toy house delivers numerous musical and other sound effects that are…Continue
Added by Kirk Borne on January 9, 2015 at 2:30pm — No Comments
In a previous article, we defined data charaterization as a “methodology for generating descriptive parameters that describe the behavior and characteristics of a data item, for use in any unsupervised learning algorithm to find features, clusters, patterns, and trends in the data without the bias of incorporating class…Continue
Added by Kirk Borne on May 31, 2014 at 11:30am — No Comments
Added by Kirk Borne on March 29, 2014 at 11:30am — No Comments
The extended annotated version of the "Big Data A to Z Glossary of my Favorite Data Science Things" is now live at: http://bit.ly/1g5NcBt
However, the original…Continue
Added by Kirk Borne on March 20, 2014 at 3:00pm — No Comments
Check out the new post on DataScienceCentral:
Added by Kirk Borne on February 28, 2014 at 5:16pm — No Comments
The application of analytics and data science methods to people is becoming an increasingly common use case for Big Data in the workplace. For example:
Added by Kirk Borne on February 15, 2014 at 11:09am — No Comments
Added by Kirk Borne on February 11, 2014 at 6:48pm — No Comments
Do you know which is the most sought after skill amongst HR professionals in 2014?
It is analytics.
More than 85% of HR professionals feel they will be able to do their job better if they pick up data analysis skills. (Source: http://jigsawacademy.com/em/2014/01/01/)
Jigsaw Academy is a leader in…Continue
Added by Kirk Borne on January 21, 2014 at 7:59am — No Comments
Here are 13 books on Machine Learning and Data Mining that are great resources, references, and refreshers for Data Scientists. (This is definitely a small selective subsample of the many excellent books available.)
Added by Kirk Borne on January 15, 2014 at 1:30pm — No Comments
Here are 13 informative and inspirational books on Big Data and Data Science. This is definitely not intended to be a comprehensive list (since a complete list of such readings would itself be a form of "Big Data", and consequently the number of possibilities is a nearly uncountable number! NOTE definition of "uncountable" = an infinite set that contains too many elements to be countable.)…Continue
Check out the blog post here:
Added by Kirk Borne on December 23, 2013 at 1:40pm — No Comments
The Comprehensive Analysis of Time Series (CATS) is an increasingly important use case in the field of Big Data analytics. Cat videos on the Internet notwithstanding, the prevalence of time series is perhaps even more universally ubiquitous in big data applications: customer purchase histories, web click logs, social events, human behaviors, speech patterns, weather reports, climate science, numerical simulation science, spread of infectious diseases, market…Continue
Added by Kirk Borne on September 6, 2013 at 9:30am — No Comments
On August 17, an article appeared in the New York Times with the title "Is Big Data an Economic Big Dud?" A colleague of mine provided a very brief summary of the article in…Continue
Added by Kirk Borne on August 18, 2013 at 1:00pm — No Comments
When we devote so much time and energy talking about Big Data, are we neglecting the important things that you can do with Small Data?
Maybe, but... probably not.Continue
The on-going Big Data media hype stirs up a lot of passionate voices. There are naysayers ("it is nothing new"), doomsayers ("it will disrupt everything"), and soothsayers…Continue
Over 100 years ago, the great science fiction writer H. G. Wells was credited with saying, "Statistical thinking will one day be as necessary for efficient citizenship as the ability to read or write." It is clear that this statement is probably more true today than ever, as Big Data and Analytics are paraded before every aspect…Continue