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Programming ML.NET: Developer Reference

Autor Dino Esposito, Francesco Esposito
en Limba Engleză Paperback – 23 mai 2022
With .NET 5's ML.NET and Programming ML.NET, any Microsoft .NET developer can solve serious machine learning problems, increasing their value and competitiveness in some of today's fastest-growing areas of software development. World-renowned Microsoft development expert Dino Esposito covers everything you need to know about ML.NET, the machine learning pipeline, and real-world machine learning solutions development. Modeled on his popular Programming ASP.NET books, this guide takes the same scenario-based approach Microsoft's team used to build the ML.NET framework itself. Esposito presents and illuminates ML.NET's dedicated mini-frameworks ("ML Tasks") for specific classes of problems, and draws on personal experience to help developers apply these in the real world, where a problem's complexity can vary widely based on data availability or the specific results you need. In a full section on ML.NET neural networks, Esposito introduces key concepts and presents realistic examples you can reuse in your own applications. Along the way, Esposito also shows how to leverage powerful Python-based machine learning tools in the .NET environment. Programming ML.NET will help you add machine learning and artificial intelligence to your tool belt, whether you have a background in these high-demand technologies or not.
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Specificații

ISBN-13: 9780137383658
ISBN-10: 0137383657
Pagini: 256
Dimensiuni: 185 x 228 x 15 mm
Greutate: 0.46 kg
Editura: Pearson Education (US)
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Notă biografică

Dino Esposito is CTO and co-founder of Crionet, a company that provides innovative software and technology to professional sports organizations. A 16-time Microsoft MVP, he has authored 20+ books, including Introducing Machine Learning; and the Microsoft Press best-seller Microsoft .NET: Architecting Applications for the Enterprise.
Francesco Esposito holds a degree in Mathematics, is the co-author of Introducing Machine Learning, and lives suspended between the depth of advanced mathematics and the intrigue of data science. He currently serves as the Head of Engineering and Data at Crionet. As an entrepreneur he founded Youbiquitous, a data analysis and software factory, and KBMS Data Force, a startup in Digital Therapy and intelligent healthcare.

Cuprins

CHAPTER 1 Artificially Intelligent Software
CHAPTER 2 An Architectural Perspective of ML.NET
CHAPTER 3 The Foundation of ML.NET
CHAPTER 4 Prediction Tasks
CHAPTER 5 Classification Tasks
CHAPTER 6 Clustering Tasks
CHAPTER 7 Anomaly Detection Tasks
CHAPTER 8 Forecasting Tasks
CHAPTER 9 Recommendation Tasks
CHAPTER 10 Image Classification Tasks
CHAPTER 11 Overview of Neural Networks
CHAPTER 12 A Neural Network to Recognize Passports
APPENDIX A Model Explainability