9780135565667-0135565669-Introducing Machine Learning (Developer Reference)

Introducing Machine Learning (Developer Reference)

ISBN-13: 9780135565667
ISBN-10: 0135565669
Edition: 1
Author: Esposito, Dino, Esposito, Francesco
Publication date: 2020
Publisher: Microsoft Press
Format: Paperback 400 pages
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Book details

ISBN-13: 9780135565667
ISBN-10: 0135565669
Edition: 1
Author: Esposito, Dino, Esposito, Francesco
Publication date: 2020
Publisher: Microsoft Press
Format: Paperback 400 pages

Summary

Acknowledged authors Esposito, Dino, Esposito, Francesco wrote Introducing Machine Learning (Developer Reference) comprising 400 pages back in 2020. Textbook and eTextbook are published under ISBN 0135565669 and 9780135565667. Since then Introducing Machine Learning (Developer Reference) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Master machine learning concepts and develop real-world solutions

Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning.

· 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you

· Explore what’s known about how humans learn and how intelligent software is built

· Discover which problems machine learning can address

· Understand the machine learning pipeline: the steps leading to a deliverable model

· Use AutoML to automatically select the best pipeline for any problem and dataset

· Master ML.NET, implement its pipeline, and apply its tasks and algorithms

· Explore the mathematical foundations of machine learning

· Make predictions, improve decision-making, and apply probabilistic methods

· Group data via classification and clustering

· Learn the fundamentals of deep learning, including neural network design

· Leverage AI cloud services to build better real-world solutions faster

About This Book

· For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills

· Includes examples of machine learning coding scenarios built using the ML.NET library

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