Performance Analysis of Machine Learning Algorithms for Intrusion Detection using -NeurosolutionsPlease guys if don’t work in Neurosolutions before, Please do not respond to this question.Instruction for project proposalEach student will provide a short proposal (max one page) including selected dataset, selected ML/DL models, and proposed tool for the implementation. The student can work on his/her project after its approval.1.Selection of datasetAndroid Malware Dataset2.Selection of ML modelEach student will select any three models of ML/DL for this project.Instruction for project methodology and results analysis1.MethodologyApply all steps of methodology as we discussed in Lecture # 4 and provide detail of every step that you have implemented in your project. You can also use a diagram to represent your methodological steps along with its detail.2.Performance AnalysisEach student will apply any three models on the selected dataset. The obtained results will be analyzed based on accuracy, error rate, sensitivity, specificity, and recall. The results of selected three models will be compared and addressed with each other as well as to similar approaches on the same dataset in recent literature.Take screenshots In Every step in Neurosolutions To use it in the report.DeliverableEach student will submit his/her project report as per the attached template via LMS. Also, Each student will have to present his/her work in a short presentation.
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