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Practical Machine Learning for Streaming Data with Python
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Table of Contents

Chapter 1:  An Introduction to Streaming Data.- Chapter 2: Concept Drift Detection in Data Streams.- Chapter 3: Supervised Learning for Streaming Data.- Chapter 4: Unsupervised Learning and Other Tools for Data Stream Mining.

About the Author

Dr. Sayan Putatunda is an experienced data scientist and researcher. He holds a Ph.D. in Applied Statistics/ Machine Learning from the Indian Institute of Management, Ahmedabad (IIMA) where his research was on streaming data and its applications in the transportation industry. He has a rich experience of working in both senior individual contributor and managerial roles in the data science industry with multiple companies such as Amazon, VMware, Mu Sigma, and more. His research interests are in streaming data, deep learning, machine learning, spatial point processes, and directional statistics. As a researcher, he has multiple publications in top international peer-reviewed journals with reputed publishers. He has presented his work at various reputed international machine learning and statistics conferences. He is also a member of IEEE.


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