Multivariate Time Series Anomaly Detection

🎯 Overview

LSTM-VAE for IoT sensor anomaly detection

This project demonstrates advanced data science techniques using world-class libraries: TensorFlow, Keras, statsmodels.

🌟 Key Features

• ✅ Production-ready implementation
• ✅ State-of-the-art algorithms
• ✅ Comprehensive visualizations
• ✅ M3/M4 Mac compatible
• ✅ Well-documented code

🛠️ Technologies

TensorFlow, Keras, statsmodels

🚀 Usage

pip install -r requirements.txt
python main.py

💡 Real-World Applications

This technique is used by leading tech companies and research institutions worldwide.

🎓 What You'll Learn

• Advanced multivariate anomaly lstm vae techniques
• Production ML pipelines
• Best practices in data science
• Industry-standard tools

📊 Expected Results

• High-quality outputs
• Interpretable results
• Production-ready artifacts

🎯 Interview Talking Points

"I implemented multivariate time series anomaly detection using TensorFlow, Keras, statsmodels. This demonstrates my expertise in advanced data science techniques and ability to work with industry-standard tools."