https://github.com/ac12644/stock-market-predictor
Forecasting the Stock Market with Watson Studio
https://github.com/ac12644/stock-market-predictor
artificial-intelligence data-science financial-markets machine-learning python stock-market
Last synced: about 1 month ago
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Forecasting the Stock Market with Watson Studio
- Host: GitHub
- URL: https://github.com/ac12644/stock-market-predictor
- Owner: ac12644
- Created: 2019-11-20T17:20:41.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-07-30T07:26:23.000Z (about 4 years ago)
- Last Synced: 2025-01-14T05:42:56.727Z (9 months ago)
- Topics: artificial-intelligence, data-science, financial-markets, machine-learning, python, stock-market
- Language: Jupyter Notebook
- Homepage:
- Size: 893 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Forecasting the Stock Market with Watson Studio
Using the IBM Watson Studio and other popular open-source Python libraries for data science, this code pattern provides an example of data science workflow which attempts to predict the end-of-day value of S&P 500 stocks based on historical data. It includes the data mining process, that uses the Quandl API – a marketplace for financial, economic and alternative data delivered in modern formats for today's analysts.
## FLOW
## STEPS
- Create a Watson Studio project.
- Assign a Cloud object storage to it.
- Load Jupyter notebook to Watson Studio.
- The sample data provided by Quandl API is imported by the notebook.
- Data imported are refined by Data Refinery and saved to Cloud object storage.
- Using SPSS modeler flow to create forecasts
- Importing the Watson Machine Learning model exported from SPSS modeler flow to Watson Machine Learning.
- Exposing Watson Machine Learning model through an API.
- Application use Watson Machine Learning API to create stock market predicitons.