Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan

Related tags

Machine Learning heroku sklearn regression-models radiation solar-energy mlops flaskapi
Overview

End-to-End Machine Learning of Historical Solar Radiation for Islamabad

Link: https://solar-isb-flaskapp.herokuapp.com/

Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.

Input: month, day, Daily_Temp, Daily_Precip, Daily_Humidity, Daily_Pressure, Daily_WindDir, Daily_WindSpeed, Daily_DNI, Daily_GHI Output: Daily_radiation

Use Json Input

{
    "month":12,
    "day":3,
    "Daily_Temp":10.98,
    "Daily_Precip":9.07,
    "Daily_Humidity":59.20,
    "Daily_Pressure":929.06,
    "Daily_WindDir":167.30,
    "Daily_WindSpeed":1.86,
    "Daily_DNI":522.20,
    "Daily_GHI":324.60
}

Results

[
    {
        "Daily_DNI": 522.2,
        "Daily_GHI": 324.6,
        "Daily_Humidity": 59.2,
        "Daily_Precip": 9.07,
        "Daily_Pressure": 929.06,
        "Daily_Temp": 10.98,
        "Daily_WindDir": 167.3,
        "Daily_WindSpeed": 1.86,
        "day": 3,
        "month": 12
    },
    {
        "solar irradiance": 92.71980683342349
    }
]

Postman

result1

Mlflow

result2

NeptuneAI

result3

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Owner
Abid Ali Awan
Love building machine learning product and working on MLOps. Currently, focusing on content creation, building brand, and startup.
Abid Ali Awan
GitHub https://solar-isb-flaskapp.herokuapp.com/
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