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Titlebook: Deep Learning Projects Using TensorFlow 2; Neural Network Devel Vinita Silaparasetty Book 2020 Vinita Silaparasetty 2020 deep learning.tens

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發(fā)表于 2025-3-21 19:57:37 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Deep Learning Projects Using TensorFlow 2
副標題Neural Network Devel
編輯Vinita Silaparasetty
視頻videohttp://file.papertrans.cn/265/264579/264579.mp4
概述Study diagrams, tables, flowcharts, and other such visual aids to interact visually with deep learning information.Troubleshoot deep learning projects.Work through deep learning projects line-by-line
圖書封面Titlebook: Deep Learning Projects Using TensorFlow 2; Neural Network Devel Vinita Silaparasetty Book 2020 Vinita Silaparasetty 2020 deep learning.tens
描述Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications.?.Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts.?.The best way to learn is by doing. You‘ll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You‘ll also work with Neural Networks and other deep learning concepts. By the end of the book, you‘ll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application.?.What You‘ll Learn.Grasp the basic process of neural networks through projects, such as creating music.Restore and colorize black and white images with deep learning processes.Who This Book Is For.Beginners new to TensorFlow and Python.?.
出版日期Book 2020
關鍵詞deep learning; tensorflow; data science; artificial intelligence; ai; python; keras; neural networks; cnn
版次1
doihttps://doi.org/10.1007/978-1-4842-5802-6
isbn_softcover978-1-4842-5801-9
isbn_ebook978-1-4842-5802-6
copyrightVinita Silaparasetty 2020
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Efficient Low-Power Hardware Design,ore powerful is a collection of neurons? That’s what we are going to discover in this chapter. Several neurons together make up a neural network. In this tutorial, we will create a multi-layer neuron and then classify the MNIST dataset with it. In Keras, a single iteration is referred to as an .. Let’s study neural networks more in detail.
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Graduate Texts in Operations ResearchThink you have a keen eye for spotting tampered images? Now what if the image has been manipulated so well that the average person is easily fooled? Neural networks can aid in finding subtle features of images and identify which ones are authentic and which ones have been modified. This is called
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