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Programming ML.Net

Dino Esposito, Francesco Esposito
Paperback | Engels | Developer Reference
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Omschrijving

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 needs
  • See how ML.NET instantiates the classic ML pipeline, and simplifies common scenarios such as sentiment analysis, fraud detection, and price prediction
  • Implement data processing and training, and "productionize" machine learning-based software solutions
  • Move from basic prediction to more complex tasks, including categorization, anomaly detection, recommendations, and image classification
  • Perform both binary and multiclass classification
  • Use clustering and unsupervised learning to organize data into homogeneous groups
  • Spot outliers to detect suspicious behavior, fraud, failing equipment, or other issues
  • Make the most of ML.NET's powerful, flexible forecasting capabilities
  • Implement the related functions of ranking, recommendation, and collaborative filtering
  • Quickly build image classification solutions with ML.NET transfer learning
  • Move 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

Specificaties

Betrokkenen

Auteur(s):
Uitgeverij:

Inhoud

Aantal bladzijden:
256
Taal:
Engels
Reeks:

Eigenschappen

Productcode (EAN):
9780137383658
Verschijningsdatum:
14/04/2022
Uitvoering:
Paperback
Formaat:
Trade paperback (VS)
Afmetingen:
183 mm x 226 mm
Gewicht:
544 g
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