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Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition Antonio Gulli, Amita Kapoor, Sujit Pal - okladka książki

Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition Antonio Gulli, Amita Kapoor, Sujit Pal - okladka książki

Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition Antonio Gulli, Amita Kapoor, Sujit Pal - audiobook MP3

Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition Antonio Gulli, Amita Kapoor, Sujit Pal - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
646
Dostępne formaty:
     PDF
     ePub
     Mobi
Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside 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 is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before.

This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML.

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O autorach książki

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.

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.

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.

Antonio Gulli, Amita Kapoor, Sujit Pal - pozostałe książki

Packt Publishing - inne książki

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