Machine Learning and Kotlin: A Practical Guide

This book is the first practical guide of its kind, combining the power of machine learning with the elegance and safety of the Kotlin language. If you are a JVM developer looking to implement modern ML algorithms without switching to Python, this book will become your indispensable assistant.

The author, Alexey Sokolov, an experienced software engineer, systematically guides the reader from basic machine learning concepts to creating full-fledged production-ready models. You will learn to use native Kotlin libraries: KotlinDL (deep learning from JetBrains), Smile (statistical learning), and DL4J (Deep Learning ecosystem on JVM).

What you will learn:

• How to prepare data: working with DataFrame, cleaning, normalization, and visualization (Kotlin for Spark, PlotlyKotlin).
• Linear regression, decision trees, and random forest – implementation from scratch and using libraries.
• Deep learning: neural networks, convolutional and recurrent architectures (KotlinDL, TensorFlow Java).
• Natural language processing: tokenization, TF-IDF, text classification (Kotlin-NLP).
• Loading and exporting models: ONNX, PMML, TensorFlow SavedModel.
• Deploying an ML model as a REST service (Ktor, Micronaut).
• Working with GPU via CUDA bindings for JVM.

Who this book is for:

• Kotlin developers looking to master Data Science without learning Python.
• Java programmers transitioning to Kotlin and seeking practical ML examples.
• Students and researchers interested in applying ML on the JVM platform.

The book contains over 50 ready-made projects and exercises with open-source code. All examples are available for download and have been tested with the latest library versions. You will start with simple linear regression for predicting housing prices and finish by creating a chatbot with an NLP module in Kotlin.

Special attention is given to performance: the author compares model training speed in Kotlin vs Python (scikit-learn) and shows how to optimize code using coroutines and multithreading. You will also learn how to integrate Kotlin models into a microservice architecture and use Apache Kafka for streaming ML.

Whether you are working on a startup or a corporate project – Kotlin and machine learning will open new horizons. Grab the book and start building smart applications today!