| Description |
1 online resource (338 pages) |
| Summary |
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. |
| Subject |
Recommender systems (Information filtering)
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Artificial intelligence.
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Machine learning.
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Python (Computer program language)
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Systèmes de recommandation (Filtrage d'information) |
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Intelligence artificielle. |
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Apprentissage automatique. |
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Python (Langage de programmation) |
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artificial intelligence. |
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Artificial intelligence. |
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Machine learning. |
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Python (Computer program language) |
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Recommender systems (Information filtering) |
| Added Author |
Yee, Hector, author.
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