KotlinConf 2019: Using Kotlin for Data Science by Roman Belov

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What makes Kotlin a great choice for data-driven systems? The fact you can use one common programming language for both data science and data engineering. With Kotlin, you can fill the gap between local exploratory data analysis and deployment of big data models in production. Not to mention that Kotlin is elegant, and its static typing allows creating neat and friendly APIs.

In this talk, we’ll make a brief overview of the Kotlin ecosystem as applied to data science, including the tooling and library aspects. Then we’ll go through a practical example covering operations on multidimensional arrays, dealing with data frames, creating charts, and deploying on clusters. The tooling will be presented using #Jupyter, #Zeppelin, and JetBrains’ Big Data Tools.

KotlinConf website: https://jb.gg/fyaze5
KotlinConf on Twitter: https://twitter.com/kotlinconf

Kotlin website: https://jb.gg/pxrsn6
Kotlin blog: https://jb.gg/7uc7ow
Kotlin on Twitter: https://twitter.com/kotlin

JetBrains Big Data Tools: https://www.jetbrains.com/help/idea/big-data-tools-support.html

#KotlinConf19 #Kotlin #DataScience #JetBrains

About the Presenter:
Software Developer @ Kotlin for Data Science

Marketing Manager @ Kotlin
Software Developer @ dotMemory

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KotlinConf 2019: Using Kotlin for Data Science by Roman Belov

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