This article was written by Monica Rogati. Monica is an independent data science executive and advisor. She built key data products and teams at Jawbone and LinkedIn; she...
In PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I, I began to discuss how data that was too big for RAM is handled in R, a memory-constrained stati...
When anybody says data science, one can immediately associate complicated technical knowledge with the term. Data scientists are considered to be highly technical profess...
In this latest Data Science Central Webinar you will get an inside look at what it means to be a Data Scientist. You’ll learn from a Practicing Data Scientist Profess...
Introduction Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (graphical and quantitative) to better under...
In a world where data really matters, everyone wants to create effective charts. But data visualization is rarely taught in schools, or covered in on-the-job training. Mo...
This article was written by John Hammink. John is Chief Evangelist for Treasure Data. An 18-year veteran of the technology and startup scene, he enjoys travel to unusua...
Tuesday of Strata Data Conference is my favorite of the four days. The calm before the storm of the keynotes and short presentations of Wednesday-Thursday, Tuesday revolv...
Labels are how humans define and categorise different concepts. There’s lots of evolutionary psychology, neuroscience and linguistics behind this, but without going int...
To understand how skills in actuarial science can be applied to investment banking we need to understand what actuarial science deals with. So what is actuarial science? ...