Machine Learning With Go

Machine Learning With Go empowers developers to enhance their machine learning capabilities by using the Go programming language. You will learn to implement various machine learning models and techniques, ranging from regression and classification to clustering and neural networks, all while leveraging Go's efficient and robust environment. This book combines practical programming examples with theoretical underpinnings to provide a balanced and actionable learning experience.

What this Book will help me do

• Learn efficient data gathering, cleaning, and preparation techniques in Go.
• Build, evaluate, and validate core machine learning models such as regression and classification.
• Analyze datasets using statistical and probabilistic techniques to gain insights.
• Implement advanced machine learning techniques like neural networks and anomaly detection with Go.
• Deploy machine learning workflows effectively, integrating analyses into scalable applications.

Author(s)

Joseph Langstaff Whitenack is a seasoned software developer specializing in Go and data engineering. With extensive professional experience in building scalable and maintainable systems, Joseph brings a practical approach to teaching machine learning through Go. He emphasizes combining best practices in software engineering with cutting-edge data science techniques to craft solutions that are both efficient and sustainable.

Who is it for?

This book is tailored for developers with a good understanding of Go who are looking to venture into machine learning and apply it in practical scenarios. Readers should be comfortable with basic Go programming and have some foundational knowledge of statistics and mathematics. Whether you're a software engineer aiming to broaden your skill set, or a data enthusiast interested in applying ML with Go, this book has you covered.