# akash13singh/lstm\_anomaly\_thesis

<https://repo.masters-masters.com/en/repos/akash13singh/lstm_anomaly_thesis>

[Home](https://repo.masters-masters.com/en) › [akash13singh](https://repo.masters-masters.com/en/owners/akash13singh) › [lstm\_anomaly\_thesis](https://repo.masters-masters.com/en/repos/akash13singh/lstm_anomaly_thesis)

akash13singh/lstm\_anomaly\_thesis has 225 stars on GitHub. Its RepoMasters card: Prototype tier. Anomaly detection for temporal data using LSTMs

| Field | Value |
| --- | --- |
| Owner | [akash13singh](https://repo.masters-masters.com/en/owners/akash13singh) |
| Stars | 225 |
| Forks | 85 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2017 |
| Topics | lstm, anomaly-detection, bayesian-optimization, time-series, recurrent-neural-networks, deep-learning, lstm-neural-networks, neural-networks |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [akash13singh/lstm\_anomaly\_thesis](https://github.com/akash13singh/lstm_anomaly_thesis) |

## Repository

Anomaly detection for temporal data using LSTMs

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.