https://github.com/himalayaashish/anomaly-detection
This project focuses on implementing anomaly detection techniques using TensorFlow to identify outliers in various datasets. The model leverages deep learning algorithms, such as autoencoders and recurrent neural networks, to effectively recognize patterns and detect deviations from normal behavior. Optimized for performance.
https://github.com/himalayaashish/anomaly-detection
encoder encoder-decoder-architecture tensorflow tensorflow2 time-series
Last synced: 3 months ago
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This project focuses on implementing anomaly detection techniques using TensorFlow to identify outliers in various datasets. The model leverages deep learning algorithms, such as autoencoders and recurrent neural networks, to effectively recognize patterns and detect deviations from normal behavior. Optimized for performance.
- Host: GitHub
- URL: https://github.com/himalayaashish/anomaly-detection
- Owner: himalayaashish
- Created: 2024-10-15T05:01:01.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-10-17T08:15:12.000Z (9 months ago)
- Last Synced: 2025-02-14T11:53:10.391Z (5 months ago)
- Topics: encoder, encoder-decoder-architecture, tensorflow, tensorflow2, time-series
- Language: Jupyter Notebook
- Homepage:
- Size: 3.28 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## Hello World! 
🚀 Welcome to my git repo :Anomaly-Detection
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#### Anomaly Detection Using TensorFlow
###### This project focuses on implementing anomaly detection techniques using TensorFlow to identify outliers in datasets. By employing deep learning models, the system is capable of recognizing patterns and flagging deviations from the norm. The project demonstrates the use of various algorithms and performance metrics to effectively detect anomalies, ensuring robust and accurate results in real-world applications.
###### This project predicts the anomaly on timeseries data conversations using the tensorflow model.
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## Installation
1. Clone this repository or download the script.
2. Install the required packages using pip:
```bash
pip install -r requirements.txt
```
```bash
python main.py
```
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### Languages and Tools
### Languages
**Python**:
**JavaScript**:
**SQL:**
### Tools
**Software Development:**
**SDLC:**
  
**Software Engineering:**
[](https://github.com/Quananhle)
[](https://github.com/Quananhle)
**Version Control:**
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