Date your Data: A Short Data-Science Love Story

It's a Monday morning; you're in your cubicle with a cup of strong coffee. An email notification breaks the silence. You have a new message: "Hey handsome, this is Ms. BigData, a free spirit, live on this vibrant planet, would you marry me and would you like to have Modbies (Models) with me?" You may feel overwhelmed by the words, feel both flattered and at the same time uncertain. It's Monday, and you've not yet hit your stride.

Cloud Machine Learning Platforms vs. Apache Spark Solutions


Cloud giants like Amazon, Google, Azure and IBM have rushed into the big data analytics cloud market.  They claim their tools will make developer tasks simple. For machine learning, they say their cloud products will free data scientists and developers from implementation details so they can focus on business logic.  


Google Cloud Machine Learning (CML)

Google Cloud Machine Learning (CML) is an effort to simplify and reduce time and cost of building a data science tech infrastructure for data science projects. It can plug into Google's other storage, querying, and data-handling products to generate machine learning models. Among the data sources is Google Cloud Dataproc - a managed Hadoop and Spark platform that is now in general availability.