A scalable flask webapp to forecast cryptocurrency prices. The forecasting model is built using stacked LSTM for one-to-one sequence of the timeseries.
Model performance:
| Cryptocurrency | Mean squared error |
|---|---|
| BTC | 1.4925e-04 |
| ETH | 6.0898e-05 |
| LTC | 5.0990e-05 |
| XRP | 2.4237e-04 |
- binance api
$ python -m pip install python-binance
- tensorflow 1.x / keras 2.2.5
- flask
- numpy
- pandas
- matplotlib
$ cd webapp
$ python3 app.py
Open your internet browser and search for "localhost:5000" in the URL box.
- add/replace trained models in webapp/cryptoviz/models/
- use API intergration for extracting prices until current timestamp to predict for future(binance lets you extract prices until 3 hours ago...best case)
- automate the prediction for continous forecast