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Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key;
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KNIME Essentials is a practical guide aimed at getting the results you want, as quickly as possible.;...
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unsupervised machine learning models Who this book is forThis book is for beginners who work with data and those who need to know how to interpret;
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This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a;
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learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications;
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, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding;
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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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of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind;
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application tools along with the processes for downloading and using them in the most optimum fashion. The content includes data analysis using;
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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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Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition;
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learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with;
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fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;
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Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and;
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to doing deep learning work with Pytorch. It is not an academic textbook and does not try to teach deep learning principles. The book will;
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algorithms for unsupervised data using deep learning concepts with R * Master the common problems faced such as overfitting of data, anomalous;
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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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Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with;
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safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then;
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This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;
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This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;
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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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Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using;
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* Explore and create intelligent systems using cutting-edge deep learning techniques * Implement deep learning algorithms and work with;
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recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python;
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Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as;
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learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also;
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Einde inhoud
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