Hands-On Automated Machine Learning

This book is for budding data scientists, data analysts, and Machine Learning enthusiasts who are new to the concept of automated machine learning. It covers auto-sklearn and MLBox for AutoML tasks, preprocessing methods, feature transformation, feature selection, generation, hyperparameter tuning, neural networks, and autoencoders. It also demonstrates how to use the available automation libraries and create and extend own custom AutoML components.

Format: Electronic book text
Length: 282 pages
Publication date: 02 April 2023
Publisher: Packt Publishing Limited

Automate data and model pipelines for faster machine learning applications

About This Book
• Build automated modules for different machine learning components
• Understand each component of a machine learning pipeline in depth
• Learn to use different open source AutoML and feature engineering platforms

Who This Book Is For
If you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You'll also find this book useful if you're an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book.

What You Will Learn
• Understand the fundamentals of Automated Machine Learning systems
• Explore auto-sklearn and MLBox for AutoML tasks
• Automate your preprocessing methods along with feature transformation
• Enhance feature selection and generation using the Python stack
• Assemble individual components of ML into a complete AutoML framework
• Demystify hyperparameter tuning to optimize your ML models
• Dive into Machine Learning concepts such as neural networks and autoencoders
• Understand the information costs and trade-offs associated with AutoML

In Detail
AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible.

In this book, you'll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature extraction, model selection, and hyperparameter tuning. You'll also explore various AutoML platforms, such as scikit-learn, TensorFlow, PyTorch, and AutoML.io, and learn how to integrate them into your machine learning projects.

By the end of this book, you'll have the skills and knowledge needed to build automated data and model pipelines for faster machine learning applications.

Weight: 540g
Dimension: 191 x 234 x 22 (mm)
ISBN-13: 9781788629898