Lecture Notes in Deep Learning (1版)

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【簡介】 The compendium provides an introduction to the theory of deep learning, from basic principles of neural network modeling and optimization to more advanced topics of neural networks as Gaussian processes, neural tangent and information theory.This unique reference text complements a largely missing theoretical introduction to neural networks without being overwhelmingly technical in a level accessible to upper-level undergraduate engineering students.Advanced chapters were designed to offer an additional intuition into the field by explaining deep learning from statistical and information theory perspectives. The book further provides additional intuition to the field by relating it to other statistical and information modeling approaches.

DEEP LEARNING FOR TARGETED TREATMENTS: TRANSFORMATION IN HEALTHCARE

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DESCRIPTION DEEP LEARNING FOR TREATMENTS The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc. Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare. Audience The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.