Summary Deep Learning with TensorFlow 2 and Keras: Regression ConvNets GANs RNNs NLP and more with TensorFlow 2 and the Keras API 2nd Edition ☆ eBook ePUB or Kindle PDF

Free read Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition

Summary Deep Learning with TensorFlow 2 and Keras: Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API, 2nd Edition ☆ eBook, ePUB or Kindle PDF ë ❰KINDLE❯ Build machine and deep learning systems with TensorFlow PDFEPUB #236 with the newly released TensorFlow and Keras for the lab production and mobile devices Key Features Introduces and then uses TensorFlow and Keras right from the start Teaches key machine and deep learning techniues Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples Book Description Deep Learning with TensorFlow and Keras Second Edition teaches neural networks and deep learning techniues alongside TensorFlow TF and Keras You'll learn how to write deep learning applications in Deep Learning PDF or the most powerful popular and scalable machine learning stack availableTensorFlow is the machine learning library of choice for professional applications while Keras offers a simple and powerful Python API for accessing TensorFlow TensorFlow provides full Keras integration making advanced machine learning easier andconvenient than ever. I have been following the work of the authors especially Amita and Antonio for many years and we have used Amita's previous book in our course at Oxford University This book extends that thinking which the authors have been building up over the years It is a good reference The book comprehensively covers coding on Python for machine learning and deeplearning with an emphasis on tensorflow 20 The book also covers some extra topics which make it a great reference such as Tensorflow in the Cloud; IoT and AutoML

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E Learning with TensorFlow 2 and ePUB #203 response Train your models on the cloud and put TF to work in real environments Explore how Google tools can automate simple ML workflows without the need for complex modeling Who this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow This book gives you the theory and practice reuired to use Keras TensorFlow and AutoML to build machine learning systems Some knowledge of machine learning is expectedTable of Contents Neural Network Foundations with TensorFlow TensorFlow x and x Regression Convolutional Neural Networks Advanced Convolutional Neural Networks Generative Adversarial Networks Word Embeddings Recurrent Neural Networks Autoencoders Unsupervised Learning Reinforcement Learning TensorFlow and Cloud TensorFlow for Mobile and IoT and TensorFlowjs An introduction to AutoML The Math Behind Deep Learning Tensor Processing Unit. enjoyed reading

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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 2nd EditionBeforeThis 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 What you will learn Build machine learning Learning with TensorFlow eBook #180 and deep learning systems with TensorFlow and the Keras API Use Regression analysis the most popular approach to machine learning Understand ConvNets convolutional neural networks and how they are essential for deep learning systems such as image classifiers Use GANs generative adversarial networks to create Learning with TensorFlow 2 and ePUB #203 new data that fits with existing patterns Discover RNNs recurrent neural networks that can process seuences of input intelligently using one part of a seuence to correctly interpret another Apply deep learning to natural human language and interpret natural language texts to produce an appropriat. This is a great book that explains in a very approachable way complex ML concepts You must have a basic understanding of ML and I would recommend this book to anyone who needs a comprehensive guide for Tensorflow and Keras The book contains as well some of the latest techniues such as capsules and much The authors have really touched upon a variety of topics and will help the reader navigate through the numerous algos available today