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Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;
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Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;
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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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With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that's paving;
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Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If;
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This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time;
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Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such;
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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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Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging;
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This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The;
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Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required;
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Speed up the design and implementation of deep learning solutions using Apache Spark Key Features Explore the world of distributed deep;
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The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used;
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Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book * Master;
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This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning;
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guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;
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guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;
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Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;
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Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network;
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machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems;
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machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems;
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New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised and;
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This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and;
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This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and;
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Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key;
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