Project: Machine Learning Based Model to Detect Anomaly in The Water
Summary:
It is a machine learning-based model that uses supervised learning algorithms and finds out the growth of the bacteria present inside water without using any expensive IoT sensors. This model can help governments and organizations identify what rivers in different states contain the presence of bacteria. Our existing model has an 87-93% accuracy rate.
Sustainable Development Goals:
Good Health and Well-Being
Clean Water and Sanitation
Skills & Resources Needed:
Skills: Python, Machine Learning.
Resources: Kaggle, gov.in for the dataset.
Tools: Jupyter notebook. Libraries: Pandas, Numpy, Matplotlib, Sklearn, Seaborn.
Post-Capsule Goals:
Private Research Program
Hobby Project
Motivation:
The bad condition of water & population growth increases drastically in India, hence there is a need to find the solution to this problem. We want to learn more about our project & how we can make our project strong at Capsule.
Team Members:
Jaya Tanwani, Project Lead
Aditi Saptarishy
Priyanka Awatramani
Shriya Sawant