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9781492045113 - Building Machine Learning Powered Applications: Going from Idea to Product di Ameisen, Emmanuel (40 risultati)
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Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Building Machine Learning Powe
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paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications : Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product (Paperback or Softback)
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Paperback or Softback. Condizione: New. Building Machine Learning Powered Applications: Going from Idea to Product. Book.
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Building Machine Learning Powered Applications: Going from Idea to Product
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Aggiungi al carrelloPaperback. Condizione: New. Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers-including experienced practitioners and novices alike-will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you:Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment.
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Building Machine Learning Powered Applications
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Building Machine Learning Powered Applications : Going from Idea to Product
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Building Machine Learning Powered Applications
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product (eng)
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Building Machine Learning Powered Applications (Paperback)
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2020
ISBN 10: 149204511X ISBN 13: 9781492045113
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Paperback. Condizione: new. Paperback. Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers-including experienced practitioners and novices alike-will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you:Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, youll build an example ML-driven application from initial idea to deployed product. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Building Machine Learning Powered Applications
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Aggiungi al carrelloPaperback. Condizione: New. Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers-including experienced practitioners and novices alike-will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you:Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment.
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Paperback. Condizione: new. New Copy. Customer Service Guaranteed.
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Building Machine Learning Powered Applications : Going from Idea to Product
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BUILDING MACHINE LEARNING POWERED APPLIC
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications : Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product
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Aggiungi al carrelloPaperback. Condizione: Brand New. 238 pages. 9.00x6.75x0.25 inches. In Stock.
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications: Going from Idea to Product
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Building Machine Learning Powered Applications
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Aggiungi al carrelloPaperback. Condizione: New. Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers-including experienced practitioners and novices alike-will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you:Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment.
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BUILDING MACHINE LEARNING POWERED APPLIC
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Building Machine Learning Powered Applications
Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers--including experienced practitioners and novices alike--will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you: Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment. 238 pp. Englisch.
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Building Machine Learning Powered Applications
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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EUR 66,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers--including experienced practitioners and novices alike--will learn the tools, best practices, and challenges involved in building a real-world ML application step by step.Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you: Define your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML models and address performance bottlenecksDeploy and monitor your models in a production environment. 238 pp. Englisch.
