Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please send contact us.
Compatible Devices: Can be read on any devices.
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 Description Go 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 for If 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.
This is a digital product.
Go Machine Learning Projects: Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go 1st Edition is written by Xuanyi Chew and published by Packt Publishing. The Digital and eTextbook ISBNs for Go Machine Learning Projects are 9781788995191, 1788995198 and the print ISBNs are 9781788993401, 1788993403.

Youth at Risk: A Prevention Resource for Counselors, Teachers, and Parents eBook
Back Rehabilitation: Core Stability Re-examined eBook
The User's Manual For The Brain Volume I eBook
Murach's SQL Server 2016 for Developers eBook
Perry and Thompson's Law and Ethics in the Business of Health Care eBook
Object Relations Brief Therapy: The Therapeutic Relationship in Short-Term Work eBook
Human Learning eBook
ggplot2 eBook
The Age of Surveillance Capitalism eBook
Gardner's Art through the Ages: A Global History, Volume I eBook
New Perspectives Microsoft Office 365 & Access 2016: Comprehensive eBook
Treatment of the Narcissistic Neuroses eBook
Elementary and Middle School Mathematics eBook
Microsoft Office Publisher 2007 Step by Step eBook
Word 2007 eBook
General Topology eBook
Encyclopedia of Knot Theory eBook
Dare to Lead eBook
Information Technology for Management: On Demand Strategies for Performance, Growth and Sustainability, Enhanced eText eBook
Shelly Cashman Series Microsoft Office 365 & Access 2016: Comprehensive eBook
Horngren's Financial & Managerial Accounting eBook
Governing Sustainable Seafood eBook
Microsoft Office Excel 2007 Step by Step eBook
Phlebotomy Handbook eBook
Codependent No More Workbook eBook
Premium Website for Hershberger/Navey-Davis/Borrás' Plazas, 5th Edition, [Instant Access], 4 terms (24 months) eBook
Modern Electric, Hybrid Electric, and Fuel Cell Vehicles, 3rd Edition eBook
The Great Chinese Art Transfer eBook
Drifting by Intention Four Epist: from within Constructive Design Research eBook
Prebles' Artforms eBook
by Design 4th Edition The Classic Guide to Word-and-Picture Communication for Art Directors, Editors, Designers, and Students eBook
Above the Fold, Revised Edition eBook 


Reviews
There are no reviews yet.