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A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series;
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Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras;
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Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep;
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approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them;
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A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the;
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This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine;
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This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine;
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sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics;
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concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data;
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This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a;
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Amazon Alexa and Google Translate possible. If you're a developer or data scientist new to NLP and deep learning, this practical guide shows you;
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Get to grips with the basics of Keras to implement fast and efficient deep-learning models About This Book * Implement various deep;
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data scientists or those who want to enter the field of AI to understand deep learning concepts. The best way to learn is by doing. You'll;
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Explore TensorFlow's capabilities to perform efficient deep learning on images Key Features Discover image processing for machine vision;
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of online learners. You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart;
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Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety;
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This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep;
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Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering;
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Deeplearning4j to implement deep learning models from scratch Explore recipes for developing, training, and fine-tuning your neural network models;
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all important deep learning concepts and their implementations Essential tips, tricks, and hacks to train a variety of deep learning models;
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to intelligently handle large and complex datasets Book DescriptionDeep learning is a subset of machine learning where datasets with several;
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on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use;
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policy-based methods with this practical guide Key Features Use TensorFlow to write reinforcement learning agents for performing;
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Build and run intelligent applications by leveraging key Java machine learning libraries About This Book * Develop a sound strategy to;
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TensorFlow guide About This Book * Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow * Explore;
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to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity;
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