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Titlebook: MATLAB Deep Learning; With Machine Learnin Phil Kim Book 2017 Phil Kim 2017 Deep Learning.machine learning.AI.artificial inteligence.big da

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發(fā)表于 2025-3-21 17:30:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱MATLAB Deep Learning
副標(biāo)題With Machine Learnin
編輯Phil Kim
視頻videohttp://file.papertrans.cn/621/620044/620044.mp4
概述Demonstrates how to counter real world problems found in big data, smart bots and more through practical examples.Broadens your understanding of neural networks, deep learning, and convolutional neura
圖書封面Titlebook: MATLAB Deep Learning; With Machine Learnin Phil Kim Book 2017 Phil Kim 2017 Deep Learning.machine learning.AI.artificial inteligence.big da
描述Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, .MATLAB Deep Learning. employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. ?.With this book, you‘ll be able to tackle some of today‘s real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage..What You‘ll Learn.Use MATLAB for deep learning.Discover neural networks and multi-layer neural networks.Work with convolution and pooling layers.Build a MNIST example with these layers.Who This Book Is For.Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful..
出版日期Book 2017
關(guān)鍵詞Deep Learning; machine learning; AI; artificial inteligence; big data; analytics; MATLAB; programming
版次1
doihttps://doi.org/10.1007/978-1-4842-2845-6
isbn_softcover978-1-4842-2844-9
isbn_ebook978-1-4842-2845-6
copyrightPhil Kim 2017
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:36:15 | 只看該作者
板凳
發(fā)表于 2025-3-22 00:32:53 | 只看該作者
Neural Network, growth in interest for Deep Learning, the importance of the neural network has increased significantly as well. We will briefly review the relevant and practical techniques to better understand Deep Learning. For those who are new to the concept of the neural network, we start with the fundamentals.
地板
發(fā)表于 2025-3-22 06:41:14 | 只看該作者
Training of Multi-Layer Neural Network,the problem involved the learning rule. As the training process is the only method for the neural network to store information, untrainable neural networks are useless. A proper learning rule for the multi-layer neural network took quite some time to develop.
5#
發(fā)表于 2025-3-22 08:59:31 | 只看該作者
or deep learning.Discover neural networks and multi-layer neural networks.Work with convolution and pooling layers.Build a MNIST example with these layers.Who This Book Is For.Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful..978-1-4842-2844-9978-1-4842-2845-6
6#
發(fā)表于 2025-3-22 13:38:07 | 只看該作者
classrooms, and offer alternative imaginings through discursive re-articulations (Hall, 1996a). Both of these tactics may be used strategically by students to further their project of appropriating new resources as they travel across transnational educational routes. The paper concludes by reflectin
7#
發(fā)表于 2025-3-22 17:13:56 | 只看該作者
Phil Kimclassrooms, and offer alternative imaginings through discursive re-articulations (Hall, 1996a). Both of these tactics may be used strategically by students to further their project of appropriating new resources as they travel across transnational educational routes. The paper concludes by reflectin
8#
發(fā)表于 2025-3-22 21:50:29 | 只看該作者
Phil Kimtice. The book helps academics, business school management, and even advanced students understand how to bring a practical focus to learning and teaching business via a holistic curriculum. The book also features a special focus on how to integrate family business perspectives to the curriculum.978-3-031-14563-6978-3-031-14564-3
9#
發(fā)表于 2025-3-23 04:29:09 | 只看該作者
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發(fā)表于 2025-3-23 07:03:38 | 只看該作者
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