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Get more from your data by creating practical machine learning
systems with Python Key Features Develop your own Python-based
machine learning system Discover how Python offers multiple
algorithms for modern machine learning systems Explore key Python
machine learning libraries to implement in your projects Book
DescriptionMachine learning allows systems to learn things without
being explicitly programmed to do so. Python is one of the most
popular languages used to develop machine learning applications,
which take advantage of its extensive library support. This third
edition of Building Machine Learning Systems with Python addresses
recent developments in the field by covering the most-used datasets
and libraries to help you build practical machine learning systems.
Using machine learning to gain deeper insights from data is a key
skill required by modern application developers and analysts alike.
Python, being a dynamic language, allows for fast exploration and
experimentation. This book shows you exactly how to find patterns
in your raw data. You will start by brushing up on your Python
machine learning knowledge and being introduced to libraries.
You'll quickly get to grips with serious, real-world projects on
datasets, using modeling and creating recommendation systems. With
Building Machine Learning Systems with Python, you'll gain the
tools and understanding required to build your own systems, all
tailored to solve real-world data analysis problems. By the end of
this book, you will be able to build machine learning systems using
techniques and methodologies such as classification, sentiment
analysis, computer vision, reinforcement learning, and neural
networks. What you will learn Build a classification system that
can be applied to text, images, and sound Employ Amazon Web
Services (AWS) to run analysis on the cloud Solve problems related
to regression using scikit-learn and TensorFlow Recommend products
to users based on their past purchases Understand different ways to
apply deep neural networks on structured data Address recent
developments in the field of computer vision and reinforcement
learning Who this book is forBuilding Machine Learning Systems with
Python is for data scientists, machine learning developers, and
Python developers who want to learn how to build increasingly
complex machine learning systems. You will use Python's machine
learning capabilities to develop effective solutions. Prior
knowledge of Python programming is expected.
This book primarily targets Python developers who want to learn and
use Python's machine learning capabilities and gain valuable
insights from data to develop effective solutions for business
problems.
This is a tutorial-driven and practical, but well-grounded book
showcasing good Machine Learning practices. There will be an
emphasis on using existing technologies instead of showing how to
write your own implementations of algorithms. This book is a
scenario-based, example-driven tutorial. By the end of the book you
will have learnt critical aspects of Machine Learning Python
projects and experienced the power of ML-based systems by actually
working on them.This book primarily targets Python developers who
want to learn about and build Machine Learning into their projects,
or who want to provide Machine Learning support to their existing
projects, and see them get implemented effectively .Computer
science researchers, data scientists, Artificial Intelligence
programmers, and statistical programmers would equally gain from
this book and would learn about effective implementation through
lots of the practical examples discussed.Readers need no prior
experience with Machine Learning or statistical processing. Python
development experience is assumed.
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