machine deep learning algorithms von mishra vishnu (6 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware -A book that covers different machine learning and deep learning algorithms specifically for lung cancer would be an excellent resource for researchers, medical professionals, and data scientists interested in leveraging artificial intelligence for medical diagnosis and treatment. While I can't provide a specific book title, I can suggest the key topics and areas such a book might cover: Introduction to Lung Cancer: The book may start with an overview of lung cancer, including its types, causes, diagnosis methods, and current treatment options. Machine Learning Fundamentals: It may cover fundamental concepts of machine learning, including supervised, unsupervised, and semi-supervised learning, as well as evaluation metrics commonly used in medical applications.Data Preprocessing and Feature Engineering: The book may discuss techniques for preprocessing medical imaging data, such as CT scans or X-rays, including image normalization, noise reduction, and feature extraction.Classification Algorithms: It would likely delve into various classification algorithms used for lung cancer detection and diagnosis, such as support vector machines (SVM), random forests, decision trees.Books on Demand GmbH, Überseering 33, 22297 Hamburg 184 pp. Englisch.

Zustand: New.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 184 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A book that covers different machine learning and deep learning algorithms specifically for lung cancer would be an excellent resource for researchers, medical professionals, and data scientists interested in leveraging artificial intelligence for medical diagnosis and treatment. While I can't provide a specific book title, I can suggest the key topics and areas such a book might cover: Introduction to Lung Cancer: The book may start with an overview of lung cancer, including its types, causes, diagnosis methods, and current treatment options. Machine Learning Fundamentals: It may cover fundamental concepts of machine learning, including supervised, unsupervised, and semi-supervised learning, as well as evaluation metrics commonly used in medical applications.Data Preprocessing and Feature Engineering: The book may discuss techniques for preprocessing medical imaging data, such as CT scans or X-rays, including image normalization, noise reduction, and feature extraction.Classification Algorithms: It would likely delve into various classification algorithms used for lung cancer detection and diagnosis, such as support vector machines (SVM), random forests, decision trees.

Zustand: New. PRINT ON DEMAND.

Zustand: New. Print on Demand.