Water treatment center data mining
Here we are going to do some data prediction in the form of regression. With some rainfall and temerature data at hand plus water treatment refinery stats, we are going to predict some other data from refinery to have a clue for future water treatment. data from 5 years are used to do some regression model train and test. 3 models used comprises of MLP neural net, random forest and gradient boosting. Although in most cased end up bad results, we would have some tolerable results base of R2 score for daily analysis versus monthly and weekly data analysis.
- Code is written by jupyter notebook on Win10
- Required libraries are listed in first code segment
- To have a copy of code and other materials you can clone at: https://github.com/mrezaa/water_treatment_data_science.git
- In jupyter notebook every code segment is easily executed with shift+Enter
- In other python interpreters you can use .py version
For any kinds of issues, feel free to contact me via email
Mohammadreza Asadi