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We apply neural networks and random forest to study geological data. In part one of the thesis, a ground water level prediction task is performed with recurrent neural networks, random forest and vector autoregression. The input data consists of weather data and other ground water level time series. The MAE and R-squared is evaluated and the variation in performance of the neural networks is discu
