Using Apache Groovy for Data Science

Webinar

Overview

Groovy is a multi-faceted, multi-paradigm programming language for the JVM that offers a wealth of features that make it ideal for transforming big data into usable solutions. 

  • It has a dynamic nature like Python, which means that it is very powerful, easy to learn, and productive.
  • It has a static nature like Java and Kotlin, which makes it fast when needed.
  • And it has first-class functional support, meaning that it offers features and allows solutions similar to Scala.

In this complimentary webinar, Object Computing Groovy Practice Lead, Paul King, reviews the key benefits of using Groovy to develop data science solutions, including integration with various JDK libraries commonly used in data science solutions.

Intended Audience

Data scientists and JVM developers interested in expanding their skills are encouraged to attend.

Prerequisites

Although everyone is welcome, we recommend attendees have at least a working familiarity with JVM development principles. No previous experience with Groovy is required.

Discover how to leverage the power of Groovy to extract meaning from large data sets.

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