Used supervised learning to study 5 high-valued equities in the technology sector. This is the capstone project for the Udacity's Machine Learning Nanodegree.
In this project we use Sklearn, Numpy, Pandas, Quandl, Python, Jupyter Notebook
In this project I apply supervised learning techniques on historical stock price data collected and distributed by Quandl.
The project has 4 files:
- capstone_report.pdf: Final Report
- capstone_proposal.pdf: Final Report
- stock_predictor.ipynb: This is the main file where my work was performed the project.
To view results Open up a browser window or tab. Click file then open. Navigate to the folder containing the project files and double click capstone_report.pdf and capstone_proposal.pdf.
To interact with ipynb file In the Terminal or Command Prompt, navigate to the folder containing the project files, and then use the command jupyter notebook stock_predictor.ipynb to open up a browser window or tab to work with your notebook.