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Titlebook: Machine Learning for Computer Scientists and Data Analysts; From an Applied Pers Setareh Rafatirad,Houman Homayoun,Sai Manoj Puduko Textboo

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21#
發(fā)表于 2025-3-25 05:04:06 | 只看該作者
Adversarial Machine Learningints are experimentally provided, such as up to 97.65% accuracy even against CW attack. Though adversarial learning’s effectiveness is enhanced, still it is shown in this work that it can be further exploited for vulnerabilities.
22#
發(fā)表于 2025-3-25 11:26:49 | 只看該作者
23#
發(fā)表于 2025-3-25 12:16:54 | 只看該作者
Transfer Learning in Mobile Healthting, and ends with a model generation module to carry out the machine learning task in the new platform or with the new user. The chapter uses . to realize the TransFall framework using time-series data.
24#
發(fā)表于 2025-3-25 18:37:57 | 只看該作者
Textbook 2022neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve.?In
25#
發(fā)表于 2025-3-25 21:51:59 | 只看該作者
data being handled.Includes numerous, practical case-studies.This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution ne
26#
發(fā)表于 2025-3-26 00:58:12 | 只看該作者
Setareh Rafatirad,Houman Homayoun,Sai Manoj PudukoDescribes traditional as well as advanced machine learning algorithms.Enables students to learn which algorithm is most appropriate for the data being handled.Includes numerous, practical case-studies
27#
發(fā)表于 2025-3-26 05:56:24 | 只看該作者
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28#
發(fā)表于 2025-3-26 10:10:47 | 只看該作者
29#
發(fā)表于 2025-3-26 16:31:09 | 只看該作者
30#
發(fā)表于 2025-3-26 20:27:24 | 只看該作者
Machine Learning for Computer Scientists and Data AnalystsFrom an Applied Pers
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