in this sectionwe learn how to apply recurrent neural networks (rnnsto the problem of stock price prediction and understand the intricacies problem statement stock price prediction is the task of forecasting the future value of given stock given the historical daily close price for & indexprepare and compare forecasting solutions & or standard and poor' index is an index comprising of stocks from different sectors of us economy and is an indicator of us equities other such indices are the dow nifty nikkei etc for the purpose of understandingwe are utilizing & indexconceptsand knowledge can be applied to other stocks as well dataset similar to gold price datasetthe historical stock price information is also publicly available for our current use casewe will utilize the pandas_datareader library to get the required & index history using yahoo finance databases we will utilize the closing price information from the dataset available though other information such as opening priceadjusted closing priceetc are also available we prepare utility function get_raw_data(to extract required information in pandas dataframe the function takes index ticker name as input for & indexthe ticker name is ^gspc the following snippet uses the utility function to get the required data in [ ]sp_df get_raw_data('^gspc'sp_close_series sp_df close sp_close_series plot(the plot for closing price is depicted in figure - figure - the & index