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Machine Learning for Biomedical Applications: With Scikit-Learn and Pytorch

AUTHOR Robinson, Emma C.; Deprez, Maria
PUBLISHER Academic Press (09/13/2023)
PRODUCT TYPE Paperback (Paperback)

Description
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more.

This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians.

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Product Format
Product Details
ISBN-13: 9780128229040
ISBN-10: 0128229047
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
More Product Details
Page Count: 304
Carton Quantity: 13
Product Dimensions: 7.40 x 0.60 x 9.20 inches
Weight: 1.36 pound(s)
Country of Origin: US
Subject Information
BISAC Categories
Computers | Artificial Intelligence - Computer Vision & Pattern Recognit
Computers | Data Science - Neural Networks
Descriptions, Reviews, Etc.
publisher marketing
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more.

This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians.

Show More
Your Price  $74.20
Paperback