This is a web application that allows users to select a cryptocurrency, select a machine learning model, and pull historical data to predict its future price. The application was built with the idea of being interactive for the user. When possible we have tried to build a product that allows the user to play with parameters.
Machine Learning Models included:
Time Series Forecasting - FB Prophet
LSTM Model
Keras & Deep Neural Network
AdaBoost
Support Vector Method
Logistic Regression
This Web App was written in Python 3.7 with the following packages and modules:
- Pandas
- numpy
- Streamlit
- yfinance
- PIL
- fbprophet
- babel.numbers
- tensorflow
- sklearn
- plotly
- matplotlib
- dotenv
This Web App was built with Python 3.7 in Jupyter Lab & VScode. If the User wants to interact with the Machine Learning Model, first install the following: To get started using this application please go to Python Download and select the version for your operating system. Then install the following libraries and packages.
sudo apt install python3-pip. This will install the pip that will make it easier to install the libraries.
pip install pandas
pip install numpy
pip install -U scikit-learn
pip install streamlit
python -m pip install -U matplotlib
pip install yfinance
pip install Pillow
pip install fbprophet
pip install hvplot
pip install --upgrade tensorflow verify installation with python -c "import tensorflow as tf;print(tf.__version__)"
pip install -U scikit-learn
pip install plotly-express
pip install python-dotenv
The File of interest is labeled crypto_signal_provider.py
To run the file open the terminal, navigate to the directory with crypto_signal_provider.py and run streamlit run crypto_signal_provider.py
This web app is pulling historical data from the Nomics API, so please have your API key in a .env file in the working directory.
Have Fun...
This code was created in 2021 for a project at (Education Services at UCB).
Additional updates/ uploads for usability was added by Christina San Diego
Additional updates/ uploads for usability was added by Stephen Thomas
Additional updates/ uploads for usability was added by Thomas Leahy
Additional updates/ uploads for usability was added by Raul Nogales
MIT License
Copyright (c) 2022 Raul
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.