Data science is a hot topic. Bart De Vylder and Pieter Buteneers offer a practical introduction that goes beyond the hype, exploring data analysis, visualization, and machine learning techniques using Python for modeling the behavior of distributed systems. You'll leave with a solid starting point to implement data science techniques in your infrastructure or domain of interest.

Data science is a hot topic. Bart De Vylder offers a practical introduction that goes beyond the hype, exploring data analysis, visualization, and machine-learning techniques using Python for modeling the behavior of distributed systems. You'll leave with a solid starting point to implement data science techniques in your infrastructure or domain of interest.

What if you had to build more models than there are data scientists in the worlda feat enterprise companies serving hundreds of thousands of businesses often have to do? Leah McGuire offers an overview of Salesforce's general-purpose machine-learning platform that automatically builds per-company optimized models for any given predictive problem at scale, beating out most hand-tuned models.

Taras Matyashovsky explains how to use Apache Spark MLlib to build a supervised learning NLP pipeline to distinguish pop music from heavy metaland have fun in the process.