Data science applications are garnering a lot of excitement, mainly because of the promise they hold in harnessing data and extracting consumable results. There are already several successful data products that have had a transformative effect on our daily lives. The ubiquitous recommender systems, e-mail spam filters, and targeted advertisements and news content have become part and parcel of life. Music and movies have become data products streaming from providers such as iTunes and Netflix. Businesses, especially in the domains such as retail, are actively pursuing ways to gain a competitive advantage by studying the market and customer behavior using a data-driven approach.

We have discussed the data analytics workflow up to the model building phase so far in the previous chapters. But the real value of a model is when it is actually deployed in a production system. The end product, the fruit of a data science workflow, is an operationalized...