overview of codes used for ML projects
Data Visualization and refinement:
autocorrelation_plots_reservoirs: creates visualizations for the autocorrelation of data normalizing_reservoir_data: normalizes the reservoir height data (a folder with different csv files an goes through and ends in creating one large file and a regression dataset) imputer_code: works to impute missing data and analyze how much missing data there is plotting_ML_features: plots features and provides visualization for feature importance giffy: turns images into a gif
Model creation (and some visualizations)
ML_codes_from_chris_discharge_predict: basic code to generate models combining codes from christian and other codes ML_forecasting_error_reservoir: most up-to-date model creator-- creates cregression dataset, time-series to tabular, forecast example, inserts pipeline into the training and evaluating, creates visualiztions for hyperparameters, visualizes outputs and erros ML_forecasting_error_discharge: similar to error_reservoir code, but for discharge prediction and iterations over a large number of models