AnAomaly detection algorithm using deep Autoencoder in python

My project is about intrusion detection or classification in IoT network traffic. I have proposed something using "Stacked Conditional Variational Autoencoder" for solving data imbalance issue and an DNN for classification which I need to implement in python. And also need to compare results with benchmark algorithms. I have 3 intrusion detection datasets.

so I need to build model along with some base models provided in the article I will provide. the base model is like this: they used"Conditional Variational Autoencoder" for generating new data by training the original data. second they merged the newly generated data with original data. 3rd they used DNN algorithm o train that merged data to classify the class/labels.

Skills: Python, Deep Learning, Computer Security, Data Science

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About the Employer:
( 0 reviews ) Kuala Lumpur, Malaysia

Project ID: #27894508

14 freelancers are bidding on average $187 for this job


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