[Feature Request]: Add Autoencoders in Machine Learning

[pavitraag]

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Feature Description

Autoencoders are a type of artificial neural network used to learn efficient codings of unlabeled data. The network is trained to compress the input into a latent-space representation and then reconstruct the output from this representation. Autoencoders are useful for dimensionality reduction, feature learning, and anomaly detection.

Use Case

In a real-time use case, a cybersecurity analyst could use Autoencoders to detect anomalies in network traffic. By training an Autoencoder on normal traffic patterns, the model can identify deviations from the norm, flagging potential security breaches or attacks, thus enhancing the organization's ability to respond to threats swiftly.

Benefits

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Priority

High

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[github-actions]

Hi @pavitraag! Thanks for opening this issue. We appreciate your contribution to this open-source project. Your input is valuable and we aim to respond or assign your issue as soon as possible. Thanks again!

[github-actions]

Hello @pavitraag! Your issue #3618 has been closed. Thank you for your contribution!