000			04061cam a2200277zu 4500
001			88856675
003			FRCYB88856675
005			20250107230148.0
006			m o d
007			cr un
008			250108s2018 fr | o|||||0|0|||eng d
020			_a9781788292061
035			_aFRCYB88856675
040			_aFR-PaCSA _ben _c _erda
100	1		_aFandango, Armando
245	0	1	_aMastering TensorFlow 1.x _c['Fandango, Armando']
264		1	_bPackt Publishing _c2018
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aFandango, Armando
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88856675 _qtext/html _a
520			_aBuild, scale, and deploy deep neural network models using the star libraries in PythonAbout This BookDelve into advanced machine learning and deep learning use cases using Tensorflow and KerasBuild, deploy, and scale end-to-end deep neural network models in a production environmentLearn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and KubernetesWho This Book Is ForThis book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book.What You Will LearnMaster advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and KerasPerform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasksBuild end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlowScale and deploy production models with distributed and high-performance computing on GPU and clustersBuild TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and RLearn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devicesSupercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow ClustersIn DetailTensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs.This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images.You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected.The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems.Style and approachStep-by-step comprehensive guide filled with advanced, real-world examples to help you master Tensorflow 1.x
999			_c70325 _d70325