Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow,
Автор: Hope Tom, Resheff Yehezkel S., Lieder Itay Название: Learning Tensorflow: A Guide to Building Deep Learning Systems ISBN: 1491978511 ISBN-13(EAN): 9781491978511 Издательство: Wiley Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.
Описание: You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.
The updated edition of this practical book uses concrete examples, minimal theory, and three production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started.
Автор: Atienza, Rowel Название: Advanced deep learning with tensorflow 2 and keras - ISBN: 1838821651 ISBN-13(EAN): 9781838821654 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.
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 ...
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
Автор: Jain Ankit, Fandango Armando, Kapoor Amita Название: Tensorflow Machine Learning Projects ISBN: 1789132215 ISBN-13(EAN): 9781789132212 Издательство: Неизвестно Рейтинг: 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.
Автор: Sasaki Kai Название: Hands-On Machine Learning with TensorFlow.js ISBN: 1838821732 ISBN-13(EAN): 9781838821739 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Hands-On Machine Learning with TensorFlow.js is a comprehensive guide that will help you easily get started with machine learning algorithms and techniques using TensorFlow.js. By the end of this book, you will be able to create and optimize your own web-based machine learning applications using practical examples.
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: McClure Nick Название: Tensorflow Machine Learning Cookbook - Second Edition ISBN: 1789131685 ISBN-13(EAN): 9781789131680 Издательство: Неизвестно Цена: 7171.00 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 About This Book - 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 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. 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 In Detail 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. Style and approach This book takes a recipe-based approach where every topic is explicated with the help of a real-world example.
Описание: This book is designed to guide you through TensorFlow 2 and how to use it effectively. Throughout the book, you will work through recipes and get hands-on experience to perform complex data computations, gain insights into your data, and more.
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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