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 triggered whenever one of the features in the house is pressed, or…

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…

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…

Check out the new post on DataScienceCentral:

Recommender Systems - past, present, and future

http://www.datasciencecentral.com/profiles/blogs/recommender-systems-past-present-and-future

Read…

For daily (and weekly) summaries of Big Data, Analytics, Statistics, and Data Science in the news, check out some of these excellent paper.li aggregations (which are just a small sample of many choices):

@analyticbridge: …

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.)

1. The Top Ten Algorithms in Data Mining, by Xindong Wu and Vipin Kumar (editors)
2. Learning from Data, by Y.Abu-Mostafa, M.Magdon-Ismail,…

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.)…

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…

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.

Looking beyond the Big Data hype helps us to …