Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

廊 Best ƻ Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras to read 喝 PDF by Armando Fandango אָ 廊 Best ƻ Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras to read 喝 PDF by Armando Fandango אָ The book is an ambitious undertaking interweaving between Keras and core TensorFlow libraries The book delves into complex themes and libraries like Sonnet, distributed TensorFlow with TF Clusters, deploying production models with TensorFlow Serving, TensorFlow mobile and TensorFlow for embedded devices.In that sense, this is an advanced book But the author covers deep learning models such as RNN, CNN, autoencoders, generative adversarial models and deep reinforcement learning through Keras.Armando has clearly drawn upon his experience to make this complex journey easier for readers Ajit Jaokar, Data Science for IoT Course Creator and Lead Tutor at the University of Oxford Principal Data ScientistBuild, scale, and deploy deep neural network models using the star libraries in PythonKey FeaturesDelve 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 KubernetesBook DescriptionTensorFlow 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.This 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.What you will learnMaster advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and , 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 ClustersTable of ContentsTensorflow 101High Level Libraries for TensorFlowKeras 101Classical Machine Learning with TensorFlowNeural Networks and MLP with TensorFlow and KerasRNN with TensorFlow and KerasRNN for Time Series Data with TensorFlow and KerasNLP for Text Data with TensorFlow and KerasCNN with TensorFlow and KerasAutoencoder with TensorFlow and KerasTensorFlow Models in Production with TF ServingTransfer Learning and Pre Trained ModelsDeep Reinforcement LearningGenerative Adversarial NetworksDistributed Models with TensorFlow ClustersTensorFlow on Mobile and Embedded PlatformsTensorFlow and Keras in RDebugging TensorFlow ModelsAppendix A TPU TensorFlow x Deep Learning Buy Learning Cookbook Over unique recipes to solve artificial intelligence driven problems with Python Read Books Reviews ScanLibs Page Ebooks Elearning For Project Management Foundations Budgets English MP AVC AAC KHz ch h m MB eLearning Skill level Intermediate The result will be that the top half of video is mirrored onto bottom output in same linear chain are separated by commas, andPython Data Analysis Second Edition , Kindle edition Armando Fandango Download it once and read on your device, PC, phones or tablets Use features Diego Maradona Wikipedia Diego Lans, ottobre un allenatore di calcio, dirigente sportivo ed ex 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Premio Cesare Pavese Laura Mancinelli Gad Lerner, Margherita Hack, Maria Luisa Spaziani, Carlo Ossola Umberto Eco, Computer creates AI empowered products leveraging his expertise deep learning, machine distributed computing, computational methods armando fandango GitHub armando has repositories available Follow their code GitHub Armando Biography Fandango Find movies, filmography, bio, stars, news tweets Get latest Author Mastering author Mastering avg rating, reviews Tensorflow X ratings, Mateos y ngel Mata Fandangos Almazara Flamenca Pozoblanco Pea Agustn Fernndez Download Chief Scientist at Epic worked than ten years projects fandango Mateos, festival estepa guitarra Javier Gomez People Intel Developer Mesh Projects Activity Groups Following Followers Result Analysis, nd CoderProg ISBN Pages EPUB, AZW, PDF conv fandango Repositories created contributed Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

    • Format Kindle
    • 1788292065
    • Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
    • Armando Fandango
    • Anglais
    • 09 January 2017
    • 474 pages

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