Deep Learning with TensorFlow (Paperback)

Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy

  • 出版商: Packt Publishing - ebooks Account
  • 出版日期: 2017-04-24
  • 定價: USD $49.99
  • 售價: $1,710
  • 語言: 英文
  • 頁數: 320
  • 裝訂: Paperback
  • ISBN: 1786469782
  • ISBN-13: 9781786469786
  • 相關標籤: TensorFlow

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產品描述

Key Features

  • Learn advanced techniques in deep learning with this example-rich guide on Google's brainchild
  • Explore various neural networks with the help of this comprehensive guide
  • Advanced guide on machine learning techniques, in particular TensorFlow for deep learning.

Book Description

Deep learning is the next step after machine learning. It is machine learning but with a more advanced implementation. As machine learning is no longer an academic topic, but a mainstream practice, deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be their guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow.

The book will take you through an understanding of the current machine learning landscape then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you'll learn how to implement various deep learning algorithms for your machine learning systems and integrate them into your product offerings such as search, image recognition, and language processing. Additionally, we'll examine its performance by optimizing it with respect to its various parameters, comparing it against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context, in order to maximize its performance.

After finishing the book, you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply some of your knowledge in a real project either in a research or commercial setting.

What you will learn

  • Provide an overview of the machine learning landscape
  • Look at the historical development and progress of deep learning
  • Describe TensorFlow and become very familiar with it both in theory and in practice
  • Access public datasets and use TF to load, process, clean, and transform data
  • Use TensorFlow on real-world data sets including images and text
  • Get familiar with TensorFlow by applying it in various hands on exercises using the command line
  • Evaluate the performance of your deep learning models
  • Quickly teach machines to learn from data by exploring reinforcement learning techniques.
  • Understand how this technology is being used in the real world by exploring active areas of deep learning research and application.