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

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. Gives a basic understanding of the most fundamental concepts within machine learning and their role in biomedical data analysis Shows how to apply a range of commonly used machine learning and deep learning techniques in biomedical problems Develops practical computational skills that are needed to manipulate complex biomedical data sets Shows how to design machine learning experiments that address specific problems related to biomedical data INDICE: Part I: Introduction and background1. Machine learning for Biomedical applications2. Programming background3. Mathematical backgroundPart II: Machine Learning Methods4. Regression5. Classification6. Ensemble methods7. Dimensionality reduction and Manifold learning8. Feature extraction and selection9. Clustering 10. Neural networksPart III: Deep Learning11. Building blocks of deep neural networks12. Common architectures13. Generative models14. The challenges of working with biomedical dataPart IV: Tricks of the trade

• ISBN: 978-0-12-822904-0
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 326
• Fecha Publicación: 01/08/2022
• Nº Volúmenes: 1
• Idioma: Inglés