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Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition

(ebook) (audiobook) (audiobook) Książka w języku 1
Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet - okladka książki

Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet - okladka książki

Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet - audiobook MP3

Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet - audiobook CD

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Bądź pierwszym, który oceni tę książkę
Stron:
698
Dostępne formaty:
     PDF
     ePub
Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available.

TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments.

This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.

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O autorach książki

Amita Kapoor od dwudziestu lat wykłada wiedzę o sieciach neuronowych na Uniwersytecie w Delhi. Interesuje się uczeniem maszynowym, sieciami neuronowymi, robotyką oraz buddyzmem i etyką w sztucznej inteligencji.

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.
Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet - pozostałe książki

Packt Publishing - inne książki

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