Deep learning recommender systems par wang (20 résultats)

paperback. Etat : Very Good.

Paperback. Etat : Very Good. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.…

Etat : New.

Etat : New.

paperback. Etat : New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Etat : As New. Unread book in perfect condition.

Paperback. Etat : New. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing.…

Paperback. Etat : new. Paperback. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing. Recommender systems are ubiquitous in our lives and are one of the main monetization methods of the Internet. This book explores how to apply deep learning technology in recommender systems, helping practitioners and researchers to understand the engineering implementation solutions of industry giants and cutting-edge progress in the field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : New.

Etat : New. In English.

Paperback. Etat : Brand New. 400 pages. 6.69x0.66x9.61 inches. In Stock.

Etat : As New. Unread book in perfect condition.

Paperback / softback. Etat : New. New copy - Usually dispatched within 3 working days.

Paperback. Etat : Brand New. 400 pages. 6.69x0.66x9.61 inches. In Stock.

Paperback. Etat : new. Paperback. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing. Recommender systems are ubiquitous in our lives and are one of the main monetization methods of the Internet. This book explores how to apply deep learning technology in recommender systems, helping practitioners and researchers to understand the engineering implementation solutions of industry giants and cutting-edge progress in the field. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing.…

Paperback. Etat : new. Paperback. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing. Recommender systems are ubiquitous in our lives and are one of the main monetization methods of the Internet. This book explores how to apply deep learning technology in recommender systems, helping practitioners and researchers to understand the engineering implementation solutions of industry giants and cutting-edge progress in the field. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Etat : New. Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of deep learning and generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related machine learning framework including model serving, model training, feature storage and data stream processing.…

Soft cover. Etat : New. BRAND NEW. book.

Taschenbuch. Etat : Neu. Deep Learning Recommender Systems | Zhe Wang (u. a.) | Taschenbuch | Englisch | 2025 | Cambridge University Press | EAN 9781009447508 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.