Apple Stock Price Prediction using GRU

Project Owner : Tharaka Sandun

Table of contents
Introduction
Import libraries and dataset
Checking Null/NA values
Preprocessing Date and convert into Datatime format
Perform Exploratory Data Analysis(EDA)
Find the duration of dataset
Monthwise comparision between Stock open and close price
Monthwise High and Low stock price
Trend comparision between stock open price, close price, high price, low price
Preprare Stock Close price
Make separate dataframe
Plot stock close price
Consider only 1 year data for prediction
Normalizing close price
Split Train and Test
Transform Close price base on Time-series-analysis forecasting requirement
Model Building (GRU)
Plotting Loss chart
Model Evaluation
Evaluation metrices RMSE, MSE and MAE
Explained variance regression score
R2 score for regression
Regression Loss Mean Gamma deviance regression loss (MGD) and Mean Poisson deviance regression loss (MPD)
Comparision of original stock close price and predicted close price
Predicting next 30 days (Testing)
Plotting last 15 days of dataset and next predicted 30 days
Plotting entire Closing Stock Price with next 30 days period of prediction