This blog aims to become a “nutshell” treatment of the subject, so those of you who work with data in a relational database management system (RDBMS) can quickly learn how to make the best possible use of a database.
This data science design pattern blog post focuses on kernel smoothing.
We hope that this blog will become a clearinghouse within the data science community for these data science design patterns, thereby extending the design-pattern tradition in software development and enterprise architecture to data science.
This post discusses how many data scientists fail to frame business problems as optimizations even after coming to the correct statistical outcome.
In this blog Mosaic discusses how businesses can take advantage of ‘small data’ before taking the plunge of collecting every data available to them.