/Stock_Price_Prediction_using_ML_Python

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Stock Price Prediction using Machine Learning

Roadmap to predicting the stock prices

  1. Take as input the data set. (For this project we've taken the Netflix data set)
  2. Then, convert the data set into a dataframe using pandas.
  3. Our basic focus in this project shall be on the Closing prices of the stock.
  4. We shall then have a brief look at the shape of the data and the data itself, using pandas.
  5. Subsequently we shal be visualizing the data using the library Matplotlib.
  6. Once we've visualized the data, then we can declare another dataframe and initialize that dataframe with just the closing prices of the Netflix stock.
  7. Then we declare another variable future_days, which shall contain the number of days for which the user wants to predict the stock prices.
  8. Subsequently, we add the future_days number of indexes into the dataframe & store them into a new column into the same dataframe, say predictions.
  9. On printing the last few columns of the new column, predictions we can values labeled as NaN, which is expected since we haven't predicted them as yet.