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https://github.com/herrfeder/udacity-data-scientist-capstone-multivariate-timeseries-prediction-webapp

This repository includes the webapp for my Udacity Data Scientist Nanodegree Capstone Project: Multivariate Timeseries Prediction for Bitcoin Price
https://github.com/herrfeder/udacity-data-scientist-capstone-multivariate-timeseries-prediction-webapp

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This repository includes the webapp for my Udacity Data Scientist Nanodegree Capstone Project: Multivariate Timeseries Prediction for Bitcoin Price

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# Multivariate-Timeseries-Prediction-Webapp

This webapp is part of the Project Repository :https://github.com/herrfeder/DataScientist/tree/master/Project_05_Capstone_Stock_Chart_Analysis



I created this seperate Repository for easier Docker deployment.



## Screenshots of Webapp



| Forecast Application | Buy And Sell Simulation | Timeshift Correlation |

|--------------------------------------|--------------------------------------|--------------------------------------|

| ![](https://github.com/herrfeder/DataScientist/raw/master/Project_05_Capstone_Stock_Chart_Analysis/images/forecast_full_view.png) | ![](https://github.com/herrfeder/DataScientist/raw/master/Project_05_Capstone_Stock_Chart_Analysis/images/buy_and_sell_sim.png) | ![](https://github.com/herrfeder/DataScientist/raw/master/Project_05_Capstone_Stock_Chart_Analysis/images/corr_timeshift.png) |



## Purpose



Building an Time Series Forecast Application to predict and forecast __Bitcoin financial data__

using supervised and unsupervised Machine Learning Approaches, this includes:

  * search, collection and of supportive Features in form of suitable Time Series (social media, other similar charts)

  * preparation, analysis, merging of Data and Feature Engineering using:

    * Correlative Analysis

    * Stationarity Analysis

    * Causality Analysis

  * Model Preprocessing and Model Fitting with this Machine Learning Algorithms:

    * supervised SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model)

    * unsupervised GRU (Gated Recurrent Unit)

  * building an Web Application using a Dash Webapp (see folder __webapp__)

    * explains my roadmap of analysis and conclusions

    * provides feature of daily forecasting using designed models

  



## Approach/Idea



It's nearly impossible to give an accurate prediction for Stock Charts or Cryptocurrency Charts for the Future.

Therefore I will only try to find signals or triggers that may announce major Movements on the Bitcoin Chart and may occur

right before the real movements.



I want to find Correlation and Causality to the Bitcoin Price by shifting all other collected time series in time.

For Example: Shifting all supportive Features one month to past gives me the freedom to look one month into the future for forcasting.

These notebooks will show my course of action:



  * [01 Correlation Analysis](https://github.com/herrfeder/DataScientist/blob/master/Project_05_Capstone_Stock_Chart_Analysis/01_corr_analysis.ipynb)

  * [02 Stationarity and Causality Analysis](https://github.com/herrfeder/DataScientist/blob/master/Project_05_Capstone_Stock_Chart_Analysis/stationarity_causality_analysis.ipynb)

  * [03 SARIMA Modelling](https://github.com/herrfeder/DataScientist/blob/master/Project_05_Capstone_Stock_Chart_Analysis/03_1_model_ARIMAX.ipynb)

  * [04 GRU Modelling](https://github.com/herrfeder/DataScientist/blob/master/Project_05_Capstone_Stock_Chart_Analysis/04_model_GRU.ipynb)

  * [05 Decision Algorithm](https://github.com/herrfeder/DataScientist/blob/master/Project_05_Capstone_Stock_Chart_Analysis/05_decision_algorithm.ipynb)

  

## Installation



An example of this web app is temporary accessible on https://federland.dnshome.de/bitcoinprediction .

Please be gentle, the resources are restricted. This app __isn't responsive__.



### Docker Instructions



1. Create directory and download Dockerfile:

    ```

    mkdir bitcoinpred_docker && cd bitcoinpred_docker

    wget https://raw.githubusercontent.com/herrfeder/Udacity-Data-Scientist-Capstone-Multivariate-Timeseries-Prediction-Webapp/master/Dockerfile

    ```



2. Build Docker Container:

    ```

    docker build . -t bitcoinpred

    ```

    

    All models are pretrained and the build process shouldn't take too long.

    

3. Run Docker Container:

    ```

    docker run -p 8050:8050 bitcoinpred:latest

    ```



4. Go to http://127.0.0.1:8050/