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and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic-and all of the;
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Wollen Sie sich A1/4ber Deep Learning informieren und vielleicht erste kleine Schritte machen, diese Technologie zu nutzen? Dann hilft;
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This text - part of the for dummies series - is suitable for anyone learning Microsoft's Visual C++, and particularly for programmers with;
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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 domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications;
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machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be;
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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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Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that;
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Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that;
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Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for;
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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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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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Written for psychology students, Social Psychology For Dummies is an accessible and entertaining introduction to the field. Social;
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Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep;
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collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes;
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collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes;
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Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics;
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New Pedagogies for Deep Learning (NDPL) provides a comprehensive strategy for systemwide transformation. Using the 6 competencies of NDPL;
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deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets;
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benefits and drawbacks of deep learning * Organizing data for your deep learning model * The deep learning stack * Measuring;
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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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learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP;
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learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP;
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the community. What You'll Learn Understand full stack deep learning using TensorFlow and gain a solid mathematical foundation for deep;
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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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helpful tips and best practices for making the most of the framework. Next, yoĆ¼ll learn how to train models effectively with transfer learning and;
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Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty;
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Einde inhoud
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