Kotlin for Data Science: Data Analysis and Machine Learning

Kotlin is traditionally associated with Android development, but its capabilities extend far beyond mobile applications. The book "Kotlin for Data Science" is the first comprehensive guide that reveals Kotlin as a powerful tool for data analysis, statistics, and machine learning. You will learn how to use Kotlin's concise syntax, its null-safety, and full compatibility with the Java ecosystem to solve real-world Data Science problems.

What is this book about?

The book is structured as a practical course that will take you from installing tools to building production-ready models. You will get acquainted with the main libraries:

• Kotlin DataFrame — for manipulating tabular data (an analog of pandas in Python);
• Kotlin Statistics — for statistical calculations and visualization;
• Kravis — for creating charts (an analog of ggplot2);
• Smile and DeepLearning4J — for machine learning and neural networks.

Who is this book for?

The publication will be useful for:

• Kotlin/Java developers who want to expand their skills towards Data Science;
• Data analysts looking to try an alternative to Python with stricter typing;
• Students studying programming and statistics;
• Machine learning engineers seeking a modern tool for prototyping.

What will you learn?

• How to set up an environment for Data Science in Kotlin (Jupyter Notebooks, IntelliJ IDEA);
• Basics of working with DataFrame: loading, filtering, grouping, merging data;
• Building charts and visual analysis;
• Applying statistical tests and distributions;
• Linear and logistic regression, decision trees, clustering;
• Integration with Java libraries (Weka, Apache Spark);
• Creating data pipelines and working with large volumes.

Each chapter contains real code examples, tasks for independent solution, and links to open datasets. You won't just read the theory — you will immediately apply it in practice. By the end of the book, you will be able to independently conduct data research, build predictive models, and integrate them into existing Kotlin projects.

The book "Kotlin for Data Science" is your guide to the world of modern data science without switching to Python. Start using the full potential of Kotlin today!