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001432952 001__ 1432952
001432952 003__ OCoLC
001432952 005__ 20230309003541.0
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001432952 019__ $$a1227387198$$a1232853392$$a1235845901$$a1240532341
001432952 020__ $$a9781484264317$$q(electronic bk.)
001432952 020__ $$a1484264312$$q(electronic bk.)
001432952 020__ $$a9781484264324$$q(print)
001432952 020__ $$a1484264320
001432952 020__ $$z1484264304
001432952 020__ $$z9781484264300
001432952 0247_ $$a10.1007/978-1-4842-6431-7$$2doi
001432952 035__ $$aSP(OCoLC)1227240640
001432952 040__ $$aYDX$$beng$$epn$$cYDX$$dERF$$dOCLCF$$dGW5XE$$dOCLCO$$dVT2$$dSFB$$dEBLCP$$dUKAHL$$dOCL$$dOCLCQ$$dOCLCO$$dCOM$$dOCLCQ
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001432952 050_4 $$aQ325.5
001432952 050_4 $$aQA76.76.M52
001432952 08204 $$a006.3/1$$223
001432952 08204 $$a004.165$$223
001432952 1001_ $$aAmaratunga, Thimira.
001432952 24510 $$aDeep learning on Windows :$$bbuilding deep learning computer vision systems on Microsoft Windows /$$cThimira Amaratunga.
001432952 260__ $$a[Place of publication not identified] :$$bApress,$$c2021.
001432952 300__ $$a1 online resource
001432952 336__ $$atext$$btxt$$2rdacontent
001432952 337__ $$acomputer$$bc$$2rdamedia
001432952 338__ $$aonline resource$$bcr$$2rdacarrier
001432952 347__ $$atext file
001432952 347__ $$bPDF
001432952 500__ $$aIncludes index.
001432952 5050_ $$aChapter 1: What is Deep Learning -- Chapter 2: Where to Start Your Deep Learning -- Chapter 3: Setting Up Your Tools -- Chapter 4: Building Your First Deep Learning Model -- Chapter 5: Understanding What We Built -- Chapter 6: Visualizing Models -- Chapter 7: Transfer Learning -- Chapter 8: Starting, Stopping and Resuming Learning -- Chapter 9: Deploying Your Model as a Web Application -- Chapter 10: Having Fun with Computer Vision -- Chapter 11: Introduction to Generative Adversarial Networks -- Chapter 12: Basics of Reinforcement Learning -- Appendix 1: A History Lesson -- Milestones of Deep Learning -- Appendix 2: Optional Setup Steps.
001432952 506__ $$aAccess limited to authorized users.
001432952 520__ $$aBuild 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. You will: 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.
001432952 650_0 $$aMachine learning.
001432952 650_0 $$aComputer vision.
001432952 650_0 $$aMicrosoft software.
001432952 650_6 $$aApprentissage automatique.
001432952 650_6 $$aVision par ordinateur.
001432952 650_6 $$aLogiciels Microsoft.
001432952 655_0 $$aElectronic books.
001432952 77608 $$iPrint version:$$aAmaratunga, Thimira.$$tDeep learning on Windows.$$d[Place of publication not identified] : Apress, 2021$$z1484264304$$z9781484264300$$w(OCoLC)1191237120
001432952 852__ $$bebk
001432952 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-1-4842-6431-7$$zOnline Access$$91397441.1
001432952 909CO $$ooai:library.usi.edu:1432952$$pGLOBAL_SET
001432952 980__ $$aBIB
001432952 980__ $$aEBOOK
001432952 982__ $$aEbook
001432952 983__ $$aOnline
001432952 994__ $$a92$$bISE