weather_Forecast

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  Few Observation derived from the dataset

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  Correlation matrix between the features from the table/DataFrame

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  Sneak Peak into the dataset

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  Monthly_Trend and high chance of weather in a month

Inspiration

As a part of MLH hack week, this is Day 3 Challenge

What it does

Based on the dataset, built a machine learning model that can predict the weather based on the given parameters

How we built it

Used a few classification models to classify between different weathers at different conditions. Different versions of Random Forests and classification models were used. Analyzed and visualized data to draw meaningful insights

Challenges we ran into

Ran into issues while modeling from the given dataset, had to feature engineer and use relevant data

What's next for weather_Forecast

Add more data and more places which can increase the ability of the model to predict the weather. Create a graphical User Interface for users to interact with the model built and deploy the model.

Built With

• matplotlib
• numpy
• pandas
• python
• scikit-learn
• seaborn