hmnshudhmn24/chrono-guard

🧠 CHRONOGUARD: Temporal Anomaly Detection & Forecasting Model

CHRONOGUARD is an advanced hybrid deep learning model for time-series anomaly detection, trend forecasting, and temporal risk visualization.
It combines Temporal Convolutional Networks (TCN), Bidirectional LSTMs, and Attention Mechanisms to learn both short-term fluctuations and long-term dependencies from sequential data.

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🚀 Features

• 🧩 Multimodal Input Support — numeric, categorical, and contextual data
• 🔍 Attention-based Anomaly Detection — identifies irregular temporal patterns in real time
• 📈 Forecast Generation — predicts next-step or multi-step sequences
• 🧠 Explainability via Heatmaps — attention and saliency visualizations for model interpretability
• 💾 Lightweight, Scalable Architecture — works on CPU/GPU and deploys easily to Hugging Face Spaces or Streamlit

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