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Titlebook: Deep Learning in Data Analytics; Recent Techniques, P Debi Prasanna Acharjya,Anirban Mitra,Noor Zaman Book 2022 Springer Nature Switzerland

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樓主: BROOD
21#
發(fā)表于 2025-3-25 04:40:54 | 只看該作者
https://doi.org/10.1007/978-1-349-26109-3 fraud in financial transactions and compare the deep learning model with several existing machine learning algorithms. The proposed model is applied on a dataset gathered in Europe in 2 days in September 2013. The accuracy evaluation metric is used to evaluate the ability of the proposed model to detect credit card fraud.
22#
發(fā)表于 2025-3-25 10:00:56 | 只看該作者
23#
發(fā)表于 2025-3-25 12:10:45 | 只看該作者
24#
發(fā)表于 2025-3-25 18:26:12 | 只看該作者
https://doi.org/10.1007/978-1-349-26109-3tion of machine learning in healthcare may help increase the efficiency of diagnosing disease and be time-saving in predicting the device. In this chapter, the different healthcare sectors and how machine learning is useful in different sectors are looked into.
25#
發(fā)表于 2025-3-25 23:49:12 | 只看該作者
26#
發(fā)表于 2025-3-26 02:46:14 | 只看該作者
27#
發(fā)表于 2025-3-26 08:08:49 | 只看該作者
28#
發(fā)表于 2025-3-26 09:53:38 | 只看該作者
Knowledge Framework for Deep Learning: Congenital Heart Diseaseques for deep learning to assist patient care by information mining methods. The attempt is to prescribe an automated strategy for diagnosing heart diseases in view of earlier information and data. However, purpose of study is to explore, detect patterns and understand the cause effective of congenital heart disease with varied parameters.
29#
發(fā)表于 2025-3-26 15:55:07 | 只看該作者
30#
發(fā)表于 2025-3-26 20:27:28 | 只看該作者
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