In this notebook, we give a simple example of data manipulation, feature extraction and model fitting using stock time series. The dataset to be used contains information about company market values over several years. This is one of the most popular kind of time series data used for regression. If one can model the value of a company as it changes over time, we can make predictions about where that company will be in the future.

Codes presented in Jupyter notebooks:

https://nbviewer.jupyter.org/github/hectoramirez/TimeSeries-ML/blob/master/TimeSeries_ML.ipynb

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