Convolutional neural networks with swift for tensorflow, Koonce, Brett
Автор: Zafar Iffat, Tzanidou Giounona, Burton Richard Название: Hands-on Convolutional Neural Networks with Tensorflow ISBN: 1789130336 ISBN-13(EAN): 9781789130331 Издательство: Неизвестно Рейтинг: Цена: 6068.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!
Автор: Lili Mou; Zhi Jin Название: Tree-Based Convolutional Neural Networks ISBN: 9811318697 ISBN-13(EAN): 9789811318696 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short propagation path, they are as efficient in learning as CNNs; yet they are also as structure-sensitive as RNNs. In this book, readers will also find a comprehensive literature review of related work, detailed descriptions of TBCNNs and their variants, and experiments applied to program analysis and natural language processing tasks. It is also an enjoyable read for all those with a general interest in deep learning.
Автор: Pujari Pradeep, Sewak Mohit, Karim MD Rezaul Название: Practical Convolutional Neural Network Models ISBN: 1788392302 ISBN-13(EAN): 9781788392303 Издательство: Неизвестно Рейтинг: Цена: 7171.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN`s best practices to implement smart ConvNet ...
Автор: Galeone, Paolo Название: Hands-on neural networks with tensorflow 2.0 ISBN: 1789615550 ISBN-13(EAN): 9781789615555 Издательство: Неизвестно Рейтинг: Цена: 7363.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a guide to the TensorFlow (TF) framework, from the static graph architecture of TF 1.x to the eager execution and all the new features introduced in TF 2.0. Neural Networks applications are developed throughout the book with the aim of making the reader capable of developing neural networks-based solutions to real problems using TF 2.0
Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size--small enough to work on the digital signal processor in an Android phone. With this practical book, you'll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware.
Authors Pete Warden and Daniel Situnayake explain how you can train models that are small enough to fit into any environment, including small embedded devices that can run for a year or more on a single coin cell battery. Ideal for software and hardware developers who want to build embedded devices using machine learning, this guide shows you how to create a TinyML project step-by-step. No machine learning or microcontroller experience is necessary.
Learn practical machine learning applications on embedded devices, including simple uses such as speech recognition and gesture detection
Train models such as speech, accelerometer, and image recognition, you can deploy on Arduino and other embedded platforms
Understand how to work with Arduino and ultralow-power microcontrollers
Use techniques for optimizing latency, energy usage, and model and binary size
Описание: This volume reports on excavations in advance of the development of a site in Norton-on-Derwent, North Yorkshire close to the line of the main Roman road running from the crossing point of the River Derwent near Malton Roman fort to York. This site provided much additional information on aspects of the poorly understood `small town` of Delgovicia.
Описание: Deep Learning is the next big thing. It is a part of machine learning. Its favorable results in application with huge and complex data is remarkable. This book will help you to get through the problems that you face during the execution of different tasks and understand hacks in deep learning, neural networks, and advanced machine learning techn...
Автор: Singh Anubhav, Bhadani Rimjhim Название: Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter ISBN: 1789611210 ISBN-13(EAN): 9781789611212 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep learning is rapidly becoming the most popular topic in the industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart AI assistant, augmented reality, and more.
Автор: Dutta Sayon Название: Reinforcement Learning with Tensorflow ISBN: 1788835727 ISBN-13(EAN): 9781788835725 Издательство: Неизвестно Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement learning allows you to develop intelligent, self-learning systems. This book shows you how to put the concepts of Reinforcement Learning to train efficient models.You will use popular reinforcement learning algorithms to implement use-cases in image processing and NLP, by combining the power of TensorFlow and OpenAI Gym.
Автор: Laborde Gant Название: Learning Tensorflow.Js: Machine Learning in JavaScript ISBN: 1492090794 ISBN-13(EAN): 9781492090793 Издательство: Wiley Рейтинг: Цена: 7126.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this guide, author Gant Laborde--Google Developer Expert in machine learning and the web--provides a hands-on end-to-end approach to TensorFlow.js fundamentals for a broad technical audience that includes data scientists, engineers, web developers, students, and researchers.
Автор: Balakrishnan Kaushik Название: TensorFlow Reinforcement Learning Quick Start Guide ISBN: 1789533589 ISBN-13(EAN): 9781789533583 Издательство: Неизвестно Рейтинг: Цена: 4964.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an essential guide for anyone interested in Reinforcement Learning. The book provides an actionable reference for Reinforcement Learning algorithms and their applications using TensorFlow and Python. It will help readers leverage the power of algorithms such as Deep Q-Network (DQN), Deep Deterministic Policy Gradients (DDPG), and ...
Автор: Mcclure, Nick Название: Tensorflow machine learning cookbook ISBN: 1786462168 ISBN-13(EAN): 9781786462169 Издательство: Неизвестно Рейтинг: Цена: 11217.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Explore machine learning concepts using the latest numerical computing library -- TensorFlow -- with the help of this comprehensive cookbook
Key Features
Your quick guide to implementing TensorFlow in your day-to-day machine learning activities
Learn advanced techniques that bring more accuracy and speed to machine learning
Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow
Book Description
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning - each using Google's machine learning library TensorFlow. This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.
What you will learn
Become familiar with the basics of the TensorFlow machine learning library
Get to know Linear Regression techniques with TensorFlow
Learn SVMs with hands-on recipes
Implement neural networks and improve predictions
Apply NLP and sentiment analysis to your data
Master CNN and RNN through practical recipes
Take TensorFlow into production
Who this book is for
This book is ideal for data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.
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