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+918050151380 https://www.trendypaper.com/s/5b1a00c581a9afd8ff765190/ms.settings/5256837ccc4abf1d39000001/5b928defbda50e15d4c76434-480x480.png" [email protected]
9789388511858- 63f9e27e541afec07f4cac08 Fundamentals Of Deep Learning & Computer Vision https://www.trendypaper.com/s/5b1a00c581a9afd8ff765190/64e4fb7dcf3bfcd7e6c7b6df/fundamentals-of-deep-learning-and-computer-vision-a-complete-original-imafpvzkxummu47u.jpg This book starts with setting up a Python virtual environment with the deep learning framework TensorFlow and then introduces the fundamental concepts of TensorFlow. Before moving on to Computer Vision, you will learn about neural networks and related aspects such as loss functions, gradient descent optimization, activation functions and how backpropagation works for training multi-layer perceptrons.
To understand how the Convolutional Neural Network (CNN) is used for computer vision problems, you need to learn about the basic convolution operation. You will learn how CNN is different from a multi-layer perceptron along with a thorough discussion on the different building blocks of the CNN architecture such as kernel size, stride, padding, and pooling and finally learn how to build a small CNN model. Relevant Links: Dork Diaries Drama Queen Books Online, Point Processes And Product Densities 168Pp Hb Books Online, Gate 2023 Civil Engineering Books Online, Prophet Books Online, Between The Two Dams Poems From Kosi Books Online, Pc Hardware And Components And Pc Architecture H1 H2 Books Online, Reusable Sticker Pad Set City Park Books Online, Learning To Express Reader Book English Reader B School Textbooks Children Book Books Online, Yoga Also For The Godless Books Online 9789388511858-
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BPB Publications
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Fundamentals Of Deep Learning & Computer Vision

Fundamentals Of Deep Learning & Computer Vision

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Author: Nikhil Singh/ Paras Ahuja

Brand: BPB Publications

ISBN: 9789388511858-
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This book starts with setting up a Python virtual environment with the deep learning framework TensorFlow and then introduces the fundamental concepts of TensorFlow. Before moving on to Computer Vision, you will learn about neural networks and related aspects such as loss functions, gradient descent optimization, activation functions and how backpropagation works for training multi-layer perceptrons.
To understand how the Convolutional Neural Network (CNN) is used for computer vision problems, you need to learn about the basic convolution operation. You will learn how CNN is different from a multi-layer perceptron along with a thorough discussion on the different building blocks of the CNN architecture such as kernel size, stride, padding, and pooling and finally learn how to build a small CNN model. Relevant Links: Dork Diaries Drama Queen Books Online, Point Processes And Product Densities 168Pp Hb Books Online, Gate 2023 Civil Engineering Books Online, Prophet Books Online, Between The Two Dams Poems From Kosi Books Online, Pc Hardware And Components And Pc Architecture H1 H2 Books Online, Reusable Sticker Pad Set City Park Books Online, Learning To Express Reader Book English Reader B School Textbooks Children Book Books Online, Yoga Also For The Godless Books Online

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