Programming ML.NET

Programming ML.NET
Dino Esposito, Francesco Esposito
RRP:
NZ$ 104.99
Our Price:
NZ$ 99.74
Paperback
Not defined - 256pg
10 Jul 2022 US
International import eta 7-19 days
9780137383658
Out Of Stock
Currently no stock in-store, stock is sourced to your order
The expert guide to creating production machine learning solutions with ML. NET! ML. NET brings the power of machine learning to all . NET developers- and Programming ML. NET helps you apply it in real production solutions. Modeled on Dino Esposito' s best-selling Programming ASP. NET, this book takes the same scenario-based approach Microsoft' s team used to build ML. NET itself. After a foundational overview of ML. NET' s libraries, the authors illuminate mini-frameworks ("ML Tasks") for regression, classification, ranking, anomaly detection, and more. For each ML Task, they offer insights for overcoming common real-world challenges. Finally, going far beyond shallow learning, the authors thoroughly introduce ML. NET neural networking. They present a complete example application demonstrating advanced Microsoft Azure cognitive services and a handmade custom Keras network- showing how to leverage popular Python tools within . NET. 14-time Microsoft MVP Dino Esposito and son Francesco Esposito show how to:Build smarter machine learning solutions that are closer to your user' s needsSee how ML. NET instantiates the classic ML pipeline, and simplifies common scenarios such as sentiment analysis, fraud detection, and price predictionImplement data processing and training, and "productionize" machine learning-based software solutionsMove from basic prediction to more complex tasks, including categorization, anomaly detection, recommendations, and image classificationPerform both binary and multiclass classificationUse clustering and unsupervised learning to organize data into homogeneous groupsSpot outliers to detect suspicious behavior, fraud, failing equipment, or other issuesMake the most of ML. NET' s powerful, flexible forecasting capabilitiesImplement the related functions of ranking, recommendation, and collaborative filteringQuickly build image classification solutions with ML. NET transfer learningMove to deep learning when standard algorithms and shallow learning aren' t enough"Buy" neural networking via the Azure Cognitive Services API, or explore building your own with Keras and TensorFlow
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.

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