Machine Learning and Kotlin. A Practical Guide

The book "Machine Learning and Kotlin" is the first practical guide of its kind, bridging the gap between the world of Data Science and modern JVM development. If you are a Kotlin developer who wants to integrate machine learning into your projects but doesn't want to switch to Python, this book is for you.

What this book is about

The book is structured as a step-by-step journey from basic ML concepts to deploying ready-made models in production. You will start with setting up the environment and getting acquainted with libraries, and finish with a full-fledged REST service on Ktor that predicts real estate prices.

What you will learn

• How to set up a Kotlin project for Data Science (Gradle, Kotlin DSL, Jupyter Notebooks)
• Basics of linear regression, decision trees, and ensemble methods in Kotlin
• Working with DeepLearning4J and DJL (Deep Java Library) for deep learning
• Data processing and visualization using Kotlin frameworks (Kravis, Smile)
• Building neural networks for image and text classification
• Integrating ML models into microservices on Ktor
• Optimizing model performance using GPU via JVM
• Testing, monitoring, and A/B experiments with ML models

Who this book is for

• Backend developers on Kotlin who want to add ML features to their applications
• Android developers interested in on-device machine learning
• Data Scientists looking to switch from Python to Kotlin for production systems
• Students studying machine learning on the JVM stack

Why Kotlin?

Kotlin is not just a language for Android. Thanks to full compatibility with Java, zero-cost abstractions, and a powerful type system, it becomes an excellent choice for Data Science. You get compile-time type safety, concise syntax, and access to the entire ecosystem of Java libraries (DL4J, ND4J, Apache Spark MLlib).

Examples from the book

Each chapter contains working code that you can run immediately. For example, you will write:

• A model for forecasting sales based on historical data
• A text sentiment classifier in Kotlin + DJL
• A service for recognizing handwritten digits (MNIST) on Ktor
• A pipeline for processing streaming data with Kafka and ML

The book "Machine Learning and Kotlin" is your bridge from the world of pure programming to the world of artificial intelligence. Start building smart applications today!