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.
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1. Introduction 2. Data preprocessing3. Machine learning techniques4. Classification examples for healthcare5. Other classification examples6. Regression examples7. Clustering examples
Offers a practical Python-based toolkit for data analysis using different machine learning techniques
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
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Produktdetaljer
ISBN
9780128213797
Publisert
2020-06-07
Utgiver
Vendor
Academic Press Inc
Vekt
1110 gr
Høyde
235 mm
Bredde
191 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
534
Forfatter