Time Series Analysis With Python

SUMMARY - This project demonstrates the implementation of several machine learning time-series forecasting techniques using Python. The task is to predict hourly tide heights for the next 7 days in the Victoria, BC harbor within the acceptable error tolerance of the NOAA, the publisher of official tide forecasts in the United States. Utilized models include XGBoost, convolutional neural network (CNN), long-short term memory network (LSTM), simple autoregression, and an autoregression type neural network. All five above models produce results within the acceptable tolerance of the NOAA. Tensorflow and Keras were used to design the neural networks.

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