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Deep Learning with TensorFlow 2 and Keras - Second Edition, Gulli Antonio, Pal Sujit, Kapoor Amita


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Автор: Gulli Antonio, Pal Sujit, Kapoor Amita
Название:  Deep Learning with TensorFlow 2 and Keras - Second Edition
ISBN: 9781838823412
Издательство: Packt Publishing
Классификация:

ISBN-10: 1838823417
Обложка/Формат: Paperback
Страницы: 646
Вес: 1.09 кг.
Дата издания: 20.12.2019
Язык: English
Издание: 2 revised edition
Размер: 190 x 237 x 40
Читательская аудитория: General (us: trade)
Подзаголовок: Regression, convnets, gans, rnns, nlp, and more with tensorflow 2 and the keras api, 2nd edition
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Поставляется из: США
Описание: ITIL(R) 4 Managing Professional CoursewareITIL 4 Managing Professional (ITIL MP) consists of four modules and is the next level of ITIL 4 to be released after ITIL 4 Foundation. ITIL MP targets IT practitioners working within technology and digital teams across businesses. The Managing Professional (MP) stream provides practical and technical knowledge about how to run successful IT-enabled services, teams and workflows. The Managing Professional Transition module is designed to allow ITIL v3 candidates to easily transition to ITIL 4. They can get the ITIL 4 Managing Professional designation through one course and one exam. The material includes;¢ Updated glossaries with highlighted changes for `Create, Deliver & Support`, `Drive Stakeholder Value` and `Direct, Plan & Improve`¢ New diagram packs with annotations for `Create, Deliver & Support`, `Drive Stakeholder Value` and `Direct, Plan & Improve`¢ Updated syllabi with highlighted changes for `Create, Deliver & Support`, `Drive Stakeholder Value` and `Direct, Plan & Improve`¢ The `High Velocity IT` manuscript, syllabus, glossary and diagram pack remain unchanged¢ Practices Overviews and the product brochure remain unchanged¢ An up-to-date Quick Reference Guide with all the information you need¢ Updated Core Manuscripts, for `Create, Deliver & Support`, `Drive Stakeholder Value` and `Direct, Plan & Improve`¢ While the changes are quite large, they have been made for streamlining or refinement only¢ There have been no changes to the examinable content or the key concepts


Tensorflow 1.X Deep Learning Cookbook

Автор: Gulli Antonio, Kapoor Amita
Название: Tensorflow 1.X Deep Learning Cookbook
ISBN: 1788293592 ISBN-13(EAN): 9781788293594
Издательство: Неизвестно
Цена: 9010.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book - Skill up and implement tricky neural networks using Google's TensorFlow 1.x - An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. - Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn - Install TensorFlow and use it for CPU and GPU operations - Implement DNNs and apply them to solve different AI-driven problems. - Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. - Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. - Use different regression techniques for prediction and classification problems - Build single and multilayer perceptrons in TensorFlow - Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. - Learn how restricted Boltzmann Machines can be used to recommend movies. - Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. - Master the different reinforcement learning methods to implement game playing agents. - GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.

Tensorflow Machine Learning Projects

Автор: Jain Ankit, Fandango Armando, Kapoor Amita
Название: Tensorflow Machine Learning Projects
ISBN: 1789132215 ISBN-13(EAN): 9781789132212
Издательство: Неизвестно
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Цена: 7171.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book will show you how to take advantage of TensorFlow`s most appealing features - simplicity, efficiency, and flexibility - in various scenarios. You will gain cutting-edge insights into using TensorFlow`s offerings for your problems and learn practical hacks to successfully implement real-world machine learning projects.


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