Pattern Recognition and Machine Learning
by Christopher M. BishopA cornerstone text, it provides a comprehensive overview of machine learning techniques, including clustering, essential for advanced data scientists.
Data Mining: Concepts and Techniques
by Jiawei Han, Micheline Kamber, Jian PeiThis classic offers deep insights into data mining, focusing on clustering methods, making it invaluable for customer segmentation.
Machine Learning: A Probabilistic Perspective
by Kevin P. MurphyAn advanced resource that covers probabilistic models and clustering algorithms, crucial for understanding complex data structures.
The Elements of Statistical Learning
by Trevor Hastie, Robert Tibshirani, Jerome FriedmanA foundational text that explores statistical learning methods, including clustering, vital for any data scientist's library.
Clustering of Time Series Data: A Survey
by A. K. Jain, M. N. Murty, P. J. FlynnThis survey provides insights into clustering time series data, essential for understanding customer behavior over time.
Data Science for Business
by Foster Provost, Tom FawcettThis book bridges data science and business strategy, offering practical insights into how clustering can enhance marketing efforts.
Deep Learning for Time Series Forecasting
by Jason BrownleeWhile focused on forecasting, it provides techniques that can be integrated with clustering for better customer segmentation.
An Introduction to Statistical Learning
by Gareth James, Daniela Witten, Trevor Hastie, Robert TibshiraniA more accessible counterpart to 'The Elements of Statistical Learning', this book covers clustering and its applications in a clear manner.