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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Go Machine Learning Projects - Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go (Paperback)
Loot Price: R1,102
Discovery Miles 11 020
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Go Machine Learning Projects - Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go (Paperback)
Expected to ship within 18 - 22 working days
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Work through exciting projects to explore the capabilities of Go
and Machine Learning Key Features Explore ML tasks and Go's machine
learning ecosystem Implement clustering, regression,
classification, and neural networks with Go Get to grips with
libraries such as Gorgonia, Gonum, and GoCv for training models in
Go Book DescriptionGo is the perfect language for machine learning;
it helps to clearly describe complex algorithms, and also helps
developers to understand how to run efficient optimized code. This
book will teach you how to implement machine learning in Go to make
programs that are easy to deploy and code that is not only easy to
understand and debug, but also to have its performance measured.
The book begins by guiding you through setting up your machine
learning environment with Go libraries and capabilities. You will
then plunge into regression analysis of a real-life house pricing
dataset and build a classification model in Go to classify emails
as spam or ham. Using Gonum, Gorgonia, and STL, you will explore
time series analysis along with decomposition and clean up your
personal Twitter timeline by clustering tweets. In addition to
this, you will learn how to recognize handwriting using neural
networks and convolutional neural networks. Lastly, you'll learn
how to choose the most appropriate machine learning algorithms to
use for your projects with the help of a facial detection project.
By the end of this book, you will have developed a solid machine
learning mindset, a strong hold on the powerful Go toolkit, and a
sound understanding of the practical implementations of machine
learning algorithms in real-world projects. What you will learn Set
up a machine learning environment with Go libraries Use Gonum to
perform regression and classification Explore time series models
and decompose trends with Go libraries Clean up your Twitter
timeline by clustering tweets Learn to use external services for
your machine learning needs Recognize handwriting using neural
networks and CNN with Gorgonia Implement facial recognition using
GoCV and OpenCV Who this book is forIf you're a machine learning
engineer, data science professional, or Go programmer who wants to
implement machine learning in your real-world projects and make
smarter applications easily, this book is for you. Some coding
experience in Golang and knowledge of basic machine learning
concepts will help you in understanding the concepts covered in
this book.
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