Introducing Machine Learning (Microsoft Press)
Wednesday, 11 March 2020

This book delivers practical knowledge to make the most of the opportunities offered by machine learning. Authors 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 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 and conclude by introducing runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning.

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Author: Dino Esposito and Francesco Esposito
Publisher: Microsoft Press
Date: March 2020
Pages: 400
ISBN: 978-0135565667
Print: 0135565669
Kindle: B084B189CB
Audience: developers interested in machine learning
Level: Intermediate/Advanced
Category: Artificial Intelligence

  • 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
  • Use AI cloud services to build better real-world solutions faster

 

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Author: Bryan O'Sullivan, John Goerzen & Don Stewart
Publisher: O'Reilly, 2008
Pages: 710
ISBN: 978-0596514983
Print: 0596514980
Kindle: B0026OR2FY
Aimed at: Developers with some familiarity with Haskell
Rating: 4
Reviewed by: Ian Elliot

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Author: Andreas C. Müller and Sarah Guido
Publisher: O'Reilly
Pages: 394
ISBN: 978-1449369415
Print:1449369413
Kindle: B01M0LNE8C
Audience: Python programmers
Rating: 4
Reviewer: Mike James

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