rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deep Learning on Windows
    sub title: Building Deep Learning Computer Vision Systems on Microsoft Windows
  name:
    name part: Amaratunga, Thimira
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2020
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (345 pages)
  abstract: Build deep learning and computer vision systems using Python, TensorFlow, Keras, OpenCV, and more, right within the familiar environment of Microsoft Windows. The book starts with an introduction to tools for deep learning and computer vision tasks followed by instructions to install, configure, and troubleshoot them. Here, you will learn how Python can help you build deep learning models on Windows. Moving forward, you will build a deep learning model and understand the internal-workings of a convolutional neural network on Windows. Further, you will go through different ways to visualize the internal-workings of deep learning models along with an understanding of transfer learning where you will learn how to build model architecture and use data augmentations. Next, you will manage and train deep learning models on Windows before deploying your application as a web application. You'll also do some simple image processing and work with computer vision options that will help you build various applications with deep learning. Finally, you will use generative adversarial networks along with reinforcement learning. After reading Deep Learning on Windows , you will be able to design deep learning models and web applications on the Windows operating system. What You Will Learn Understand the basics of Deep Learning and its history Get Deep Learning tools working on Microsoft Windows Understand the internal-workings of Deep Learning models by using model visualization techniques, such as the built-in plot_model function of Keras and third-party visualization tools Understand Transfer Learning and how to utilize it to tackle small datasets Build robust training scripts to handle long-running training jobs Convert your Deep Learning model into a web application Generate handwritten digits and human faces with DCGAN (Deep Convolutional Generative Adversarial Network) Understand the basics of Reinforcement Learning Who This Book Is For AI developers and enthusiasts wanting to…
  note: Amaratunga, Thimira.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web. 2021.
  note: Mode of access: World Wide Web.
  note: Made available through: Safari, an O'Reilly Media Company.
  identifier: 9781484264317
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 161220
    record change date: 20260128204553.1
    record identifier: in00004440839