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Cover: 9780128229040 | Machine Learning for Biomedical Applications | Robinson (u. a.) | Buch
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Machine Learning for Biomedical Applications
With Scikit-Learn and PyTorch
Taschenbuch von Emma C. Robinson (u. a.)
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor
Dr Maria Deprez is a Lecturer in Medical Imaging in the Department of Perinatal Imaging & Health at the School of Biomedical Engineering & Imaging Sciences. Her Research interests are in motion correction and reconstruction of fetal and placental MRI, Spatio-temporal models of developing brain, segmentation, registration, atlases, machine learning, and deep learning
Inhaltsverzeichnis
1. Programming in Python
2. Machine Learning Basics
3. Regression
4. Classification
5. Dimensionality reduction
6. Clustering
7. Ensemble methods
8. Feature extraction and selection
9. Introduction to Deep Learning
10. Neural Networks
11. Convolutional Neural Networks
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780128229040
ISBN-10: 0128229047
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Robinson, Emma C.
Deprez, Maria
Hersteller: Elsevier Science Publishing Co Inc
Maße: 191 x 237 x 18 mm
Von/Mit: Emma C. Robinson (u. a.)
Erscheinungsdatum: 13.09.2023
Gewicht: 0,636 kg
Artikel-ID: 119651386
Über den Autor
Dr Maria Deprez is a Lecturer in Medical Imaging in the Department of Perinatal Imaging & Health at the School of Biomedical Engineering & Imaging Sciences. Her Research interests are in motion correction and reconstruction of fetal and placental MRI, Spatio-temporal models of developing brain, segmentation, registration, atlases, machine learning, and deep learning
Inhaltsverzeichnis
1. Programming in Python
2. Machine Learning Basics
3. Regression
4. Classification
5. Dimensionality reduction
6. Clustering
7. Ensemble methods
8. Feature extraction and selection
9. Introduction to Deep Learning
10. Neural Networks
11. Convolutional Neural Networks
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780128229040
ISBN-10: 0128229047
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Robinson, Emma C.
Deprez, Maria
Hersteller: Elsevier Science Publishing Co Inc
Maße: 191 x 237 x 18 mm
Von/Mit: Emma C. Robinson (u. a.)
Erscheinungsdatum: 13.09.2023
Gewicht: 0,636 kg
Artikel-ID: 119651386
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