Stockprice_prediction_with_sklearn

Use scikit learn, keras and tensor flow for some basic predictions.

Please clone the git repository the usual way by running

$ git clone https://github.com/stefan-stein/Stockprice_prediction_with_sklearn.git

Then open up the jupyter notebook to see the sample code.

Disclaimer: These models are not fit to be used for actual stock price prediction. This notebook is more of a showcase of the various regression models available in scikit-learn and tensorflow, as well as exploring how to best visualize the predictions.

Models used in this notebook

In this notebook we explore the performance of three regression models:

• Ridge regression from scikit-learn, i.e. sklearn.linear_model.Ridge
• Gradient boosting from scikit-learn, i.e. sklearn.ensemble.GradientBoostingRegressor
• And finally an LSTM neural network using keras with tensorflow backend.