It is extremely hard to predict the stock market. Stock market prediction is the act of triying to determine the future value of a company stock. Predicting such an unstable market in which many external factors come into play is very difficult. The aim of this project is to use deep learning to forecast the prices quoted on the New York Stock Market, the world's largest stock exchange by trading volume and the second largest by number of listed companies. The project is focused on predicting the stock price of the company Netflix.
The project is entirely carried out in Python and the dataset used is freely available on Kaggle and consists of the daily prices (open, close, higher, lower) of all the companies listed on the New York Stock Exchange from 2010 to 2016.
The whole project can be found on the Jupyter Notebook with Python code, output and comments.