Groovy and Data Science Workshop Part 4: Optimization Classification

Groovy and Data Science Workshop
Paul King

A presentation from ApacheCon @Home 2020
https://apachecon.com/acah2020/

Groovy is a powerful multi-paradigm programming language for the JVM that offers a wealth of features that make it ideal for many data science and big data scenarios.

* Groovy has a dynamic nature like Python, which means that it is very powerful, easy to learn, and productive. The language gets out of the way and lets data scientists write their algorithms naturally.
* Groovy has a static nature like Java and Kotlin, which makes it fast when needed. Its close alignment with Java means that you can often just cut-and-paste the Java examples from various big data solutions and they'll work just fine in Groovy.
* Groovy has first-class functional support, meaning that it offers features and allows solutions similar to Scala. Functional and stream processing with immutable data structures can offer many advantages when working in parallel processing or clustered environments.
This workshop reviews the benefits of using Groovy to develop data science solutions, including integration with various JDK libraries commonly used in data science solutions including libraries for data manipulation, machine learning, plotting and various big data solutions for scaling up these algorithms. Math/Data Science libraries covered include: Weka, Smile, Tablesaw, Apache Commons Math, Jupyter/Beakerx notebooks, Deep Learning4J. Libraries for scaling/concurrency include: Apache Spark, Apache Ignite, Apache MXNet, GPars, Apache Beam.
Slides for this workshop are here: https://speakerdeck.com/paulk/groovy-data-science
Github repo for this workshop is here: https://github.com/paulk-asert/groovy-data-science
Setup involves either:
1. Just follow along online from the repo page which has links to beakerx notebooks, or
2. Clone the repo and have a recent Java (JDK11 is recommended) and your favourite IDE (optional) installed
Paul King is a JavaOne Rockstar who has been contributing to open source projects for nearly 30 years. He is an active committer on numerous projects including Groovy, GPars and Gradle. Paul speaks at international conferences, publishes in software magazines and journals, and is a co-author of Manning’s best-seller: Groovy in Action, 2nd Edition. He is also VP Apache Groovy and Chair of the Apache Groovy PMC.