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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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Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook;
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, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands;
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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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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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TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using;
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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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you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you'll cover the basic;
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apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learn Build machine learning and deep;
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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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Ideal for Machine Learning and Deep Learning enthusiasts who are interested in programming with Python using Tensorflow 2.0 in the Jupyter;
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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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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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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 an effective image classification system using the power of CNNs Leverage TensorFlow's capabilities to perform efficient deep learning;
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TensorFlow Enterprise Discover how to accelerate the machine learning development life cycle using enterprise-grade services Manage Google's cloud;
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learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects;
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industry focused real-world use cases Tackle time series modeling in R Apply deep learning using Keras and TensorFlow in R Who This Book is For;
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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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Deep Learning Using Python and TensorFlow includes valuable case studies across professional domains, including banking, insurance, e-commerce;
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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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Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition;
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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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reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x. By the end of this TensorFlow book, you'll have;
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material in this book and become a TensorFlow programmer! What You'll Learn Develop using deep learning algorithms Build deep;
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Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow;
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methods in economics and machine learning, including regression analysis, natural language processing, and dimensionality reduction. TensorFlow;
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