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Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;
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more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples;
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Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with;
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Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing;
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This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train;
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Become a machine learning pro! Google TensorFlow has become the darling of financial firms and research organizations, but the;
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Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook;
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practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow;
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Skip the theory and get the most out of Tensorflow to build production-ready machine learning models Key Features Exploit the features;
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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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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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overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You;
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Use TensorFlow Enterprise with other GCP services to improve the speed and efficiency of machine learning pipelines for reliable and stable;
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As part of the best-selling Pocket Primer series, this book provides an overview of the major concepts to program using TensorFlow 2. The;
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compatible APIs across the TensorFlow ecosystem Learn and implement best practices for building data ingestion pipelines using TF 2.0 APIs Migrate;
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you get started creating machine learning applications? The answer is TensorFlow, a new open source machine learning library from;
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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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reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and;
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A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 Key Features Understand the basics of machine;
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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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This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning and how to;
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* Enter the new era of second-generation machine learning with Python with this practical and insightful guide * Set up TensorFlow 1.x for actual;
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learning library, TensorFlow. This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data;
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This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn;
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Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book * Skill up;
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well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow;
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TensorFlow ist Googles herausragendes Werkzeug fA1/4r das maschinelle Lernen, und dieses Buch macht es zugAnglich, selbst wenn Sie bisher;
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