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learning systems with TensorFlow 2 and the Keras API Use Regression analysis, the most popular approach to machine learning Understand ConvNets;
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will find it useful. What You Will Learn * Become familiar with the basics of the TensorFlow machine learning library * Get to know;
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these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended;
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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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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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technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book;
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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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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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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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integrate with TensorFlow. js to create intelligent web apps. The most common and accessible platform users interact with everyday is their web;
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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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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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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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in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the;
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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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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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This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will;
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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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Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning;
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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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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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Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;
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Einde inhoud
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