JulianMcAuley
Personalized Machine Learning
Personalized Machine Learning
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Excellent- More about Personalized Machine Learning
This book provides an introduction to common principles and methods for designing personalized predictive models in various settings and modalities,revising traditional machine learning models and presenting advanced techniques such as matrix factorization,deep learning,and generative modeling. Case studies and hands-on projects will give readers understanding and experience with large-scale real-world datasets.
Format: Hardback
Length: 350 pages
Publication date: 03 February 2022
Publisher: Cambridge University Press
Machine learning systems play a significant role in our daily lives by providing personalized predictions across various domains, including entertainment, social connections, purchases, and health. These predictions are made using a diverse range of data modalities, such as sequences of clicks, text, images, and social interactions. This comprehensive book aims to introduce fundamental principles and methodologies for designing personalized predictive models across different settings and modalities.
The book begins by revisiting traditional machine learning models and adapting them to settings involving user data. It then delves into advanced principles, including matrix factorization, deep learning, and generative modeling, to develop powerful tools for personalized prediction. The book concludes with a thorough examination of the implications and risks associated with deploying personalized predictive systems.
To enhance the learning experience, the book includes a series of case studies spanning various domains, such as e-commerce and healthcare. Hands-on projects and code examples are provided to allow readers to apply their knowledge and gain practical experience working with large-scale real-world datasets. By covering a wide range of applications, this book equips readers with the skills and knowledge necessary to design and implement personalized predictive models that can improve our lives and businesses.
Weight: 632g
Dimension: 159 x 235 x 28 (mm)
ISBN-13: 9781316518908
Edition number: New ed
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