Short-term Stock Market Price Prediction using Deep Learning Models
This blog is about short-term stock market price trend prediction using a comprehensive deep learning LSTM model. Results show that t he model achieves overall high accuracy for stock market trend prediction . The following end-to-end sequence provides the detailed Python/Jupyter workflow from data processing to prediction, including the data exploration: 1. Data Preparation Phase #import libraries import pandas as pd import numpy as np # To remove the scientific notation from numpy arrays np.set_printoptions(suppress=True) # install the nsepy library to get stock prices !pip install nsepy ############################################ # Getting Stock data using nsepy library from nsepy import get_history from datetime import datetime startDate=datetime(2021, 1,1) endDate=datetime(2022, 10, 3) # Fetching the data StockData=get_history(symbol='INFY', start=startDate, end=endDate) print(StockData.shape) StockData.head() # Creating a column as date StockData['TradeDa