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amirsoahil101/
Rainfall_Prediction_Dashboard

Name: Rainfall_Prediction_Dashboard
Availability: InStock

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🌧️ Rainfall Prediction Dashboard using Machine Learning

A production-grade, highly intuitive Streamlit web application that predicts the likelihood of rainfall based on climate and atmospheric features. The underlying engine utilizes a robust Logistic Regression pipeline, achieving an impressive accuracy metric on test evaluations.

📱 Application Interface

Here is a preview of the interactive dashboard layout:

🚀 Key Features

Production-Ready UI: Clean, split-column layout with helpful descriptive tooltips for users.
Resilient Architecture: Embedded error handling (try-except chains) to capture missing project dependencies or serialization asset errors gracefully without breaking the layout skeleton.
Preprocessed Compatibility: Seamlessly integrates standard scaler mappings directly on user entry streams.

📊 Model Performance

Algorithm: Logistic Regression
Model Accuracy: 92%
Features Included: Temperature, Dew Point, Humidity, Sea Level Pressure, Wind Direction, Solar Radiation, and Wind Speed.

📁 Repository Structure

text

├── app.py              # Main Streamlit Application UI Code
├── UI.png              # Screenshot of the Application Interface
├── model.pickle        # Trained Logistic Regression Model Weights
├── scale.pickle        # Fitted StandardScaler Instance
├── column.pickle       # Reference list of verified training columns
└── requirements.txt    # Application Dependency Manifest

clone command

git clone https://huggingface.co/amirsoahil101/Rainfall_Prediction_Dashboard