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Personalized Machine Learning
Buch von Julian McAuley
Sprache: Englisch

60,30 €*

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Beschreibung
Explains methods behind machine learning systems to personalize predictions to individual users, from recommendation to dating and fashion.
Explains methods behind machine learning systems to personalize predictions to individual users, from recommendation to dating and fashion.
Über den Autor
Julian McAuley has been a Professor at UC San Diego since 2014. Personalized Machine Learning is the main research area of his lab, with applications ranging from personalized recommendation, to dialog, healthcare, and fashion design. He regularly collaborates with industry on these topics, including with Amazon, Facebook, Microsoft, Salesforce, and Etsy. His work has been selected for several awards, including an NSF CAREER award, and faculty awards from Amazon, Salesforce, Facebook, and Qualcomm, among others.
Inhaltsverzeichnis
1. Introduction; Part I. Machine Learning Primer: 2. Regression and feature engineering; 3. Classification and the learning pipeline; Part II. Fundamentals of Personalized Machine Learning: 4. Introduction to recommender systems; 5. Model-based approaches to recommendation; 6. Content and structure in recommender systems; 7. Temporal and sequential models; Part III. Emerging Directions in Personalized Machine Learning: 8. Personalized models of text; 9. Personalized models of visual data; 10. The consequences of personalized machine learning; References; Index.
Details
Erscheinungsjahr: 2022
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 338
ISBN-13: 9781316518908
ISBN-10: 1316518906
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: McAuley, Julian
Hersteller: Cambridge University Press
Maße: 235 x 157 x 23 mm
Von/Mit: Julian McAuley
Erscheinungsdatum: 12.01.2022
Gewicht: 0,643 kg
preigu-id: 120756106
Über den Autor
Julian McAuley has been a Professor at UC San Diego since 2014. Personalized Machine Learning is the main research area of his lab, with applications ranging from personalized recommendation, to dialog, healthcare, and fashion design. He regularly collaborates with industry on these topics, including with Amazon, Facebook, Microsoft, Salesforce, and Etsy. His work has been selected for several awards, including an NSF CAREER award, and faculty awards from Amazon, Salesforce, Facebook, and Qualcomm, among others.
Inhaltsverzeichnis
1. Introduction; Part I. Machine Learning Primer: 2. Regression and feature engineering; 3. Classification and the learning pipeline; Part II. Fundamentals of Personalized Machine Learning: 4. Introduction to recommender systems; 5. Model-based approaches to recommendation; 6. Content and structure in recommender systems; 7. Temporal and sequential models; Part III. Emerging Directions in Personalized Machine Learning: 8. Personalized models of text; 9. Personalized models of visual data; 10. The consequences of personalized machine learning; References; Index.
Details
Erscheinungsjahr: 2022
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 338
ISBN-13: 9781316518908
ISBN-10: 1316518906
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: McAuley, Julian
Hersteller: Cambridge University Press
Maße: 235 x 157 x 23 mm
Von/Mit: Julian McAuley
Erscheinungsdatum: 12.01.2022
Gewicht: 0,643 kg
preigu-id: 120756106
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