{"product_id":"9780137383627","title":"Programming ML.NET","description":"\u003cp\u003e\u003cb\u003eThe expert guide to creating production machine learning solutions with ML.NET!   \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e        \u003c\/p\u003e \u003cp\u003eML.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.\u003c\/p\u003e \u003cp\u003e\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e14-time Microsoft MVP Dino Esposito and son Francesco Esposito show how to:\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cul\u003e  \u003cli\u003eBuild smarter machine learning solutions that are closer to your user's needs\u003c\/li\u003e  \u003cli\u003eSee how ML.NET instantiates the classic ML pipeline, and simplifies common scenarios such as sentiment analysis, fraud detection, and price prediction\u003c\/li\u003e  \u003cli\u003eImplement data processing and training, and “productionize” machine learning–based software solutions\u003c\/li\u003e  \u003cli\u003eMove from basic prediction to more complex tasks, including categorization, anomaly detection, recommendations, and image classification\u003c\/li\u003e  \u003cli\u003ePerform both binary and multiclass classification\u003c\/li\u003e  \u003cli\u003eUse clustering and unsupervised learning to organize data into homogeneous groups\u003c\/li\u003e  \u003cli\u003eSpot outliers to detect suspicious behavior, fraud, failing equipment, or other issues\u003c\/li\u003e  \u003cli\u003eMake the most of ML.NET's powerful, flexible forecasting capabilities\u003c\/li\u003e  \u003cli\u003eImplement the related functions of ranking, recommendation, and collaborative filtering\u003c\/li\u003e  \u003cli\u003eQuickly build image classification solutions with ML.NET transfer learning\u003c\/li\u003e  \u003cli\u003eMove to deep learning when standard algorithms and shallow learning aren't enough\u003c\/li\u003e  \u003cli\u003e“Buy” neural networking via the Azure Cognitive Services API, or explore building your own with Keras and TensorFlow\u003c\/li\u003e \u003c\/ul\u003e  \u003cp\u003e\u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e \u003cp\u003e  \u003c\/p\u003e","brand":"Pearson Education","offers":[{"title":"Default Title","offer_id":46570086793457,"sku":"9780137383627","price":47.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0674\/5433\/7265\/files\/9780137383627_p0.jpg?v=1765841562","url":"https:\/\/shop.barnesandnoble.com\/products\/9780137383627","provider":"Barnes \u0026 Noble","version":"1.0","type":"link"}