https://github.com/sureshbeekhani/autoencoders
This project is a practice implementation of an autoencoder, The primary use case for this autoencoder is for anomaly detection in sales data, but it can be adapted for other purposes. The autoencoder compresses the input data into a lower-dimensional representation and then reconstructs the original input from this representation.
https://github.com/sureshbeekhani/autoencoders
autoencoder convolutional-autoencoder data-compression data-reconstruction deep-learning denoising-autoencoder generative-models image-processing latent-space machine-learning neural-networks vanilla-autoencoder variational-autoencode
Last synced: 7 months ago
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This project is a practice implementation of an autoencoder, The primary use case for this autoencoder is for anomaly detection in sales data, but it can be adapted for other purposes. The autoencoder compresses the input data into a lower-dimensional representation and then reconstructs the original input from this representation.
- Host: GitHub
- URL: https://github.com/sureshbeekhani/autoencoders
- Owner: SURESHBEEKHANI
- License: gpl-3.0
- Created: 2024-07-06T04:14:09.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-17T12:29:38.000Z (11 months ago)
- Last Synced: 2025-05-17T12:29:44.567Z (11 months ago)
- Topics: autoencoder, convolutional-autoencoder, data-compression, data-reconstruction, deep-learning, denoising-autoencoder, generative-models, image-processing, latent-space, machine-learning, neural-networks, vanilla-autoencoder, variational-autoencode
- Language: Jupyter Notebook
- Homepage:
- Size: 477 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE