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This book provides an accessible introduction to the foundations of machine learning and deep learning in medicine for medical students;
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Provides a comprehensive overview of machine learning and deep learning techniques for biomedical imaging Includes thoracic imaging;
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Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals;
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the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you;
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Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;
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you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how;
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Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Key;
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from text, image and speech * Guide to set-up deep learning models using CPU and GPU Who This Book Is For Data science professionals or;
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. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal;
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it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a;
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the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience;
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the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience;
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Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and more Key Features Deep Learning;
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Deep learning has already achieved remarkable results in many fields. Now it's making waves throughout the sciences broadly and the life;
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fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized in this book, which offers a;
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have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher;
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learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and;
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Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries;
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, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation;
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, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation;
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and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;
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and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;
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Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for;
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Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS;
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This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine;
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This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine;
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