Kotlin is a JVM platform language that fills two practical data science needs: you can use it to prototype models quickly, then effectively move those models into production. Data science values languages that provide a fast turnaround. This is why R and Python are the usual language choices for the data science domain. However, as data science continues to integrate into mainstream software development workflows, a gap has appeared. It's one thing to hack together a proof-of-concept model; it's another to move it into the “business is evolving and models must be refactored” world of production. Kotlin closes the gap. Backed by Jetbrains and Google, Kotlin expands on the simplicity, conciseness, and elegance of Python, but carries the power, robustness, and scalability of Java and Scala. In this course, you'll get a detailed overview of Kotlin and discover why it's becoming the go-to practical language of choice for production-oriented data scientists and engineers. Learners should have Intellij IDEA and JDK, Python experience, and a little experience with basic analytics (Pandas, R, Excel, SQL, etc.).
- Learn about Kotlin, the emerging language of choice for data science and analytics
- Understand the data science software-engineering gap and see how Kotlin can close it
- Discover how well Kotlin moves models from proof-of-concept to production
- Master the distinctions among Kotlin, Scala, and Python; then see why data engineers choose Kotlin
- Learn how to utilize Kotlin’s tooling and environment with Intellij IDEA
- Discover how Kotlin’s innovative nullable type system avoids null-related runtime errors
- Explore how static typing and object-oriented programming make clear, bug resistant models
- Gain experience using Kotlin for data science purposes like functions and data classes
Thomas Nield is a senior-level business analyst for Southwest Airlines where he's developed multiple reactive applications that generate revenue for the entire airline network. A master programmer working in Java, Kotlin, ReactiveX, Python, and database design, Thomas writes a popular blog covering ReactiveX concepts, maintains RxJavaFX and RxKotlinFX, and is the author of the O'Reilly title Getting Started with SQL.
Table of contents
- Why Kotlin for Data Science?
- Comparison of Kotlin to Other Platforms
- Kotlin Basics - Your First Kotlin Application
- Kotlin Basics - Types and Operators
- Kotlin Basics - Functions
- Kotlin Basics - Nullable Types
- Kotlin Basics - Project Navigation and Organization
- Boolean Logic and "if"
- "when" Expressions
- Data Classes
- Ranges and Loops
- Collection Operators
- Factory Patterns and Companion Objects
- Title: From Data Science to Production with Kotlin: The Basics
- Release date: November 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491998199
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