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Example of prediction
Inspiration
Because water is essential for life, sometimes we don't know if water is potable or not for us, for solve this, we have a tool that based on a kaggle database, can predict if water is potable or dangerous for us.
What it does
Based on a kaggle water potability database, generate a machine learning model based on k-means, and predict if water is potable or dangerous for us.
How we built it
We use python with k-means library, and pandas to import .csv file (database), and create a model of k-means based on this data. then using jupyter-notebook widgets, read data for create a prediction using the k-means generated model.
Accomplishments that we're proud of
The model can predict if water is potable or not, and until I am new on machine learning I can do the model and works.
What we learned
To use the k-means model, to predict new values based on data.
What's next for Water Potability ML
Probably to clean more data, and see what can be making noise on the ML model created.
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