Predicting Tesla stock prices with RNNs
This is an example on how to use RNNs to predict stock market price.
I've used LSTM as a type of RNN.
This LSTM cell image is from Colah's blog.
Dataset
The dataset used in this project is Tesla stocks history (From August 2014 - August 2017). I have downloaded this file from Google stocks, but you have csv file inside the project folder. Name of the file is tesla_stocks.csv.
Install
Supported Python version
- Python version used in this project: 3.5+
Libraries used
- Pandas 0.18.0
- Numpy 1.10.4
- Matplotlib 1.5.1
- Scikit-learn 0.17.1
- TensorFlow 1.2.0
Code
This project has 2 different implementations.
-
Implementation by using Tensorflow built-in RNN functions. This is a version which you would use in an industry. This implementation can be found inside tensorflow_lstm.ipynb.
-
Implementation number 2 has been done without using any high level functions from TensorFlow. This implementation is good for understanding how RNNs are working. This implementations is in file lstm_from_scratch_tensorflow.ipynb.
Run
To run this project you will need some software, like Anaconda, which provides support for running .ipynb files (Jupyter Notebook).
After making sure you have that, you can run from a terminal or cmd next lines:
For the 1st version of the code:
ipython notebook tensorflow_lstm.ipynb
or
jupyter notebook tensorflow_lstm.ipynb
For the 2nd version of the code:
ipython notebook lstm_from_scratch_tensorflow.ipynb
or
jupyter notebook lstm_from_scratch_tensorflow.ipynb
License
IT License
Copyright (c) 2017 Luka Anicin
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.