Go (Golang) for Data Science: A Practical Guide

Go (Golang) is rapidly conquering the world of backend development, but few know that this language is a powerful tool for Data Science. The book "Go (Golang) for Data Science" is the first practical guide that will show you how to use Go's speed, simplicity, and concurrency to solve data analysis tasks, build pipelines, and even machine learning.

What is this book about?

The book covers the complete data workflow in Go: from loading and cleaning to visualization and model deployment. You will learn how to efficiently process large volumes of data using goroutines and channels, and get acquainted with the Go ecosystem for Data Science.

• Data Basics: reading CSV, JSON, Parquet, working with databases (PostgreSQL, ClickHouse), and stream processing.
• Analysis Libraries: a detailed breakdown of packages gonum, gota, dataframe, and goNum for statistics and linear algebra.
• Machine Learning in Go: implementing regression, classification, clustering using goLearn, go-ml, and gorgonia (neural networks).
• Visualization: plotting charts via go-echarts, plot, and integration with Jupyter Notebook through gophernotes.
• Production Pipelines: creating microservices for ML, working with Kafka, gRPC, and deploying models in Docker.

Who is this book for?

• Data Scientists and analysts who want to go beyond Python and leverage Go's performance for processing millions of records in real time.
• Go developers looking to expand their skills towards data analysis and machine learning.
• Data Engineers building high-load ETL pipelines and needing a fast and reliable tool.

What will you learn?

• How to load, clean, and transform data 10 times faster than in Python.
• How to use Go's concurrency for parallel dataset processing.
• How to build machine learning models without Python and deploy them in production.
• How to integrate Go with popular Data Science tools: Jupyter, Pandas (via gopandas), TensorFlow (via tfgo).
• Real-world cases: log processing, time series prediction, recommendation systems.

The book contains dozens of code examples that can be run immediately, and practical assignments to reinforce the material. You will get ready-made project templates and links to open-source repositories.

Whether you are working with terabytes of logs or building a model for a startup — Go will give you the speed of C and the simplicity of Python. Start your journey in Data Science with Go today!