Subject archive for "data-engineering"

Data is all around us, from the spreadsheets we analyse on a daily basis, to the weather forecast we rely on every morning or the webpages we read. In many cases, the data we consume is simply given to us, and a simple glance is enough to make a decision. For example, knowing that the chance of rain today is 75% all day makes me take my umbrella with me. In many other cases, the data provided is so rich that we need to roll up our sleeves and we may use some exploratory analysis to get our heads around it. We have talked about some useful packages to do this exploration in a previous post.

Danger of Big Data

Special thanks to Addison-Wesley Professional for permission to excerpt the following "Software Architecture" chapter from the book, Machine Learning in Production. This chapter excerpt provides data scientists with insights and tradeoffs to consider when moving machine learning models to production. Also, if you’re interested in learning about how Domino provides an API endpoint for your model, check out this video tutorial on the Domino Support site.

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise.