Practical Machine Learning for Streaming Data with Python: Design, Develop, and Validate Online or Incremental Machine Learning Models in a Streaming Data Context
Language: English
Published by APress, 2021
- Softcover
- New
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
AbeBooks seller since June 14, 2006
Condition: New
£ 35.23
Quantity: 2 available
Add to basketItem description from seller
Seller Inventory # B9781484268667
- Title
- Practical Machine Learning for Streaming Data with Python: Design, Develop, and Validate Online or Incremental Machine Learning Models in a Streaming Data Context
- Author
- Sayan Putatunda
- Publisher
- APress
- Publication year
- 2021
- Condition
- New
- Binding
- Paperback / softback
- Language
- English
- ISBN 10
- 1484268660
- ISBN 13
- 9781484268667
- Item weight
- 184 grams
You'll start with an introduction to streaming data, the various challenges associated with it, some of its real-world business applications, and various windowing techniques. You'll then examine incremental and online learning algorithms, and the concept of model evaluation with streaming data and get introduced to the Scikit-Multiflow framework in Python. This is followed by a review of the various change detection/concept drift detection algorithms and the implementation of various datasets using Scikit-Multiflow.
Introduction to the various supervised and unsupervised algorithms for streaming data, and their implementation on various datasets using Python are also covered. The book concludes by briefly covering other open-source tools available for streaming data such as Spark, MOA (Massive Online Analysis), Kafka, and more.
- Understand machine learning with streaming data concepts
- Review incremental and online learning
- Develop models for detecting concept drift
- Explore techniques for classification, regression, and ensemble learning in streaming data contexts
- Apply best practices for debugging and validating machine learning models in streaming data context
- Get introduced to other open-source frameworks for handling streaming data.
"Synopsis" may belong to another edition of this title.
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.
"About the title" may belong to another edition of this title.
THE SAINT BOOKSTORE
Southport, United Kingdom
AbeBooks seller since June 14, 2006
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