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Machine Learning for Biomedical Applications - Research Book

Machine Learning for Biomedical Applications - Research Book

Good Research Book in Machine Learning for Biomedical Applications

Author(s) Name:  Maria Deprez, Emma Robinson

About the Book:

   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.

Table of Contents

  • 1. Machine learning for Biomedical applications
  • 2. Programming background
  • 3. Mathematical background
  • 4. Regression
  • 5. Classification
  • 6. Ensemble methods
  • 7. Dimensionality reduction and Manifold learning
  • 8. Feature extraction and selection
  • 9. Clustering
  • 10. Neural networks
  • 11. Building blocks of deep neural networks
  • 12. Common architectures
  • 13. Generative models
  • 14. The challenges of working with biomedical data

    • ISBN:  9780128229040

    Publisher:  Elsevier

    Year of Publication:  2022

    Book Link:  Home Page Url