Hands-On Automated Machine Learning

"Hands-On Automated Machine Learning" introduces developers and data professionals to the exciting field of AutoML, where repetitive machine learning tasks like data preprocessing, feature selection, and hyperparameter tuning are automated to save time and enhance productivity. Through this book, learn how you can leverage Python and libraries like auto-sklearn to build your own AutoML pipelines.

What this Book will help me do

• Gain a comprehensive understanding of automated machine learning (AutoML) systems conceptually and practically.
• Build streamlined machine learning pipelines using Python libraries like auto-sklearn and MLBox.
• Automate common ML tasks such as feature selection, transformation, and hyperparameter optimization.
• Develop skills to integrate and deploy automated components in real-world machine learning projects.
• Explore practical datasets and implement AutoML techniques to boost project efficiency and model performance.

Author(s)

None Das and None Mert Cakmak are experienced machine learning practitioners with deep expertise in Python development and automation frameworks. They bring their practical knowledge and educational background to create a resource that is approachable yet rich in technical detail. Their writing aims to empower readers to replicate and extend learned concepts.

Who is it for?

This book is perfect for aspiring data scientists, analysts, machine learning enthusiasts, and professionals new to AutoML who want to deepen their expertise in automating ML workflows. If you currently use Python and wish to learn how to integrate AutoML into your projects to save time and effort, this book is an ideal fit.