Isbn: 9781492045113 - building machine learning powered applications: going from idea to product (15 Ergebnisse)

Paperback. Zustand: Fair. 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.

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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

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Paperback. Zustand: Brand New. 238 pages. 9.00x6.75x0.25 inches. In Stock.

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Zustand: 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.&Uumlber den Autor.

Taschenbuch. Zustand: Neu. Building Machine Learning Powered Applications | Going from Idea to Product | Emmanuel Ameisen | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | O'Reilly Media | EAN 9781492045113 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: 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 managersincluding experienced practitioners and novices alikewill 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 problem- Build your first end-to-end pipeline quickly and acquire an initial dataset- Train and evaluate your ML models and address performance bottlenecks- Deploy and monitor your models in a production environmentLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.…

Taschenbuch. Zustand: 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 managersincluding experienced practitioners and novices alikewill 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 problem- Build your first end-to-end pipeline quickly and acquire an initial dataset- Train and evaluate your ML models and address performance bottlenecks- Deploy and monitor your models in a production environment.…

Taschenbuch. Zustand: 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 managersincluding experienced practitioners and novices alikewill 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 problem- Build your first end-to-end pipeline quickly and acquire an initial dataset- Train and evaluate your ML models and address performance bottlenecks- Deploy and monitor your models in a production environment Englisch.…