文献类型： 会议论文
第一作者： Balázs Tóth
作者： Balázs Tóth 1 ; Szandra Anna Laczi 2 ; Valéria Póser 3 ;
作者机构： 1.John von Neumann Faculty of Informatics, Óbuda University, Budapest, Hungary
2.Doctoral School of Applied Informatics and Applied Mathematics, Obuda University, Budapest, Hungary
3.John von Neumann Faculty of Informatics, Biomatics and Applied Intelligence Institution, Óbuda University, Budapest, Hungary
关键词： Training;Visualization;Image analysis;Unsolicited e-mail;Neural networks;Filtering algorithms;Natural language processing;Feeds;Intelligent systems;Informatics
会议名称： [ "International Symposium on Intelligent Systems and Informatics" , "IEEE International Symposium on Intelligent Systems and Informatics"]
主办单位：
页码： 227-232
摘要： This paper outlines the development of an artificial intelligence spam detection solution using PyTorch framework. The neural network itself is based on a feed forward neural network where the model will be trained on different datasets to show the overall results of the spam detection. Also the model architecture, used parameters and the training process will be shown from zero to finish and what algorithms used too. At the end of the paper, it will show the developed model efficiently identified and detected messages that exhibited suspicious characteristics.
分类号： tp18-53
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