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Hands-On Automated Machine Learning - A beginner's guide to building automated machine learning systems using AutoML and Python (Paperback)
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Hands-On Automated Machine Learning - A beginner's guide to building automated machine learning systems using AutoML and Python (Paperback)
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Automate data and model pipelines for faster machine learning
applications Key Features 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 Book DescriptionAutoML 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 selection, model
training, model optimization, and much more. In addition to this,
it demonstrates how you can use the available automation libraries,
such as auto-sklearn and MLBox, and create and extend your own
custom AutoML components for Machine Learning. By the end of this
book, you will have a clearer understanding of the different
aspects of automated Machine Learning, and you'll be able to
incorporate automation tasks using practical datasets. You can
leverage your learning from this book to implement Machine Learning
in your projects and get a step closer to winning various machine
learning competitions. 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 Who this book is forIf 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.
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