Objective: Predict water quality using multiple models produced using different methods, and finally compare the results.
List of methods used:
- Convolutional Neural Network
- Image Segmentation
- Gradient Boosting
- Adaboost
- XGBoost
- Radial basis function
- Multilayer perceptron
- Multiple linear regression