I'm doing a presentation on Kotlin and Data Science for the Chicago Kotlin Users Group on April 29! A basic understanding of Kotlin is helpful, but not necessary to enjoy and learn useful information about the world of Kotlin, Data Science, and interactive Web notebooks!
The world of Data Science heavily uses Python and Python libraries such as NumPy and Pandas. While Python is a great platform, it does have some drawbacks - one of which is performance. As Java developers, we enjoy the familiarity of the JVM and the constellation of tools and libraries available for this high-performance platform.
One of the key advantages of Apache Zeppelin, which we'll cover in this session, is that it's built on Java - so you can use any Java library you want. As you can imagine, Big Data tools like Apache Spark (which of course is also written in Java) are easy to integrate into Zeppelin.
We'll work through a couple of examples in Kotlin, and use some Kotlin libs and explain how to pull these libs into Zeppelin. The ability to work in this environment is something I like to call a super repl - fast, interactive coding with continuous feedback and visualization of what you're coding!
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