Building recommendation systems in Python and JAX

• Verfasst von: Bischof, Bryan [VerfasserIn]
• Verfasst von: Yee, Hector [VerfasserIn]
• Titel: Building recommendation systems in Python and JAX
• Titelzusatz: hands-on production systems at scale
• Verf.angabe: Bryan Bischof and Hector Yee
• Ausgabe: [First edition].
• Verlagsort: Sebastopol, CA
• Verlag: O'Reilly Media, Inc.
• Jahr: 2023
• Umfang: 1 online resource (338 pages)
• Schlagwörter: (s)Empfehlungssystem / (s)Maschinelles Lernen / (s)Python <Programmiersprache> / (s)JAX
• Datenträger: Online-Ressource
• Dokumenttyp: Einführung
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe: Bischof, Bryan: Building recommendation systems in Python and JAX. - First edition. - Beijing : O'Reilly, 2023. - xviii, 332 Seiten
• Sach-SW: COM005030
• Sach-SW: COM060180
• Sach-SW: COM094000
• Sach-SW: COMPUTERS / Artificial Intelligence
• Sach-SW: COMPUTERS / Data Processing / Storage & Retrieval
• Sach-SW: COMPUTERS / Logic Design
• Sach-SW: COMPUTERS / Programming / Software Development
• Sach-SW: COMPUTERS / Programming Languages / Python
• Sach-SW: Machine learning
• Sach-SW: Maschinelles Lernen
• K10plus-PPN: 1868807509
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4399861959
• Lokale URL Inst.: Zum Volltext

Abstract

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way. In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, and Weights & Biases.