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--small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems;
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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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on TensorFlow Who This Book Is For This book is ideal for data scientists who are familiar with C++ or Python and perform machine;
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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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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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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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book is forData scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will;
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solutions with TensorFlow. It starts with an overview of machine learning concepts and moves on to the essentials needed to begin using;
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-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you;
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focus of this book is on basic programming instructions used in machine learning and deep learning. Includes companion files with source code;
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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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fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;
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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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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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. 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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techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow;
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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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, image classification, and object detection Develop deep learning models on cloud platforms and optimize them using TensorFlow Lite and the;
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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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standard reference on machine learning for economics and finance. This book focuses on economic and financial problems with an empirical dimension;
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historical development and progress of deep learning * Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x;
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learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on;
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related to machine learning Includes separate appendices for regular expressions, Keras, and TensorFlow 2;
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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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