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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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Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook;
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Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation;
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book is forData scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will;
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machine learning algorithms. Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement;
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TensorFlow on your computer Learn the fundamentals of statistical regression and neural networks Visualize the machine learning process 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;
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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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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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Tackle common commercial machine learning problems with Google's TensorFlow 1.x library and build deployable solutions. About This Book;
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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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very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep;
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learning, linear and logical regression, etc. Covers TensorFlow 2 and previous versions that run with TF2. Includes companion files with source;
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build high-efficiency data input pipelines Perform transfer learning and fine-tuning with TensorFlow Hub Define and train networks to solve;
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Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This;
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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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. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement;
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Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for;
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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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Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;
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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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This book is designed to provide the reader with basic Python3 programming concepts related to machine learning. The first four chapters;
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TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R. As in the first edition, the authors have kept the fine;
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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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Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If;
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Who This Book Is For Beginners, practitioners, and hard-cored developers who want to master machine and deep learning with TensorFlow 2;
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