Machine Learning Engineer Nanodegree Capstone Project

Machine Learning Approach to Stock Price Prediction

This project aims to build a long-short term memory networks model to predict stock price.
The data set used is historical prices and volumes of all the companies in S&P 500, which is queried from Alpha Vantage and is stored in the data.csv file.
The model is built using Keras with Tensorflow backend.
All the code and result can be found in the code.ipynb.
The project proposal is the proposal.pdf, and the final report is the report.pdf. The rmd files with the same names are the rmarkdown files that generate the report.