How to use Scala for data science

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These days we widely use Scala in Data Science and Machine Learning fields. Scala is a small, fast, and efficient multi-paradigm programming language built on a compiler. The JVM(Java Virtual Machine) is Scala’s main advantage . Scala code is first compiled by a Scala compiler, which generates bytecode, which is then transported to the JVM for output generation.

The guide then delves into:

  • Why we learn Scala for data science
  • Scala: A quick guide
  • Scala as a data science tool
  • Data types in Scala
  • Expressions in Scala
  • Functions and methods in Scala
  • Classes and objects in Scala
  • Packages and imports
  • Parallel collection In Scala:
  • Scala’s benefits
  • Scala’s drawbacks

Scala was built to implement scalable solutions to crunch big data in order to produce actionable insights. Scala’s static types help complicated applications avoid problems, and its JVM and JavaScript runtimes allow you to construct high-performance systems with simple access to a vast library ecosystem. Scala is a multi-stream wonder of the twentieth century. It has experienced phenomenal growth since its inception, and it is without a doubt one of the most in-demand programming languages. Good read.

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Tags scala programming data-science akka big-data