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Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows Michael Bironneau, Toby Coleman - okladka książki

Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows Michael Bironneau, Toby Coleman - okladka książki

Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows Michael Bironneau, Toby Coleman - audiobook MP3

Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows Michael Bironneau, Toby Coleman - audiobook CD

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168
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Do przechowalni

Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go.
The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced.
The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum.
The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring.
At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones.

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O autorach książki

Michael Bironneau is an award-winning mathematician and experienced software engineer. He holds a PhD in mathematics from Loughborough University and has worked in several data science and software development roles. He is currently technical director of the energy AI technology company, Open Energi.
Toby Coleman is an experienced data science and machine learning practitioner. Following degrees from Cambridge University and Imperial College London, he has worked on the application of data science techniques in the banking and energy sectors. Recently, he held the position of innovation director at cleantech SME Open Energi, and currently provides machine learning consultancy to start-up businesses.

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