Practical Machine Learning for Data Analysis Using Python
Language: English
Published by Elsevier Science Publishing Co Inc, US, 2020
- Softcover
- New
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
AbeBooks seller since June 11, 2025
Condition: New
£ 149.89
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Add to basketItem description from seller
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. …
Seller Inventory # LU-9780128213797
- Title
- Practical Machine Learning for Data Analysis Using Python
- Author
- Abdulhamit Subasi
- Publisher
- Elsevier Science Publishing Co Inc, US
- Publication year
- 2020
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0128213795
- ISBN 13
- 9780128213797
- Item weight
- 1,110 grams
Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
- Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas
- Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data
- Explores important classification and regression algorithms as well as other machine learning techniques
- Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features
"Synopsis" may belong to another edition of this title.
About the Author
Abdulhamit Subasi is a highly specialized expert in the fields of Artificial Intelligence, Machine Learning, and Biomedical Signal and Image Analysis and Security. His extensive expertise in applying machine learning across diverse domains is evident in his numerous contributions, including the authorship of multiple book chapters, as well as the publication of a substantial body of research in esteemed journals and conferences.
"About the title" may belong to another edition of this title.
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