Stock Price Prediction using Time Series Data

Project : Stock Price Prediction Using Time Series Analysis and Forecasting

Description : Conducted a comparative analysis of ARIMA AND LSTM model for time series analysis, focus on stock market data.
Investigated the impact of parameter tuning, feature selection, and model architecture on forecasting accuracy.

Technology Used :
Programming Language : Python
Data Analysis Libraries : Pandas, Numpy
Machine learning Libraries : scikit-learn
Data Visualization Tools: Matplotlib, Seaborn
Data Source: Yahoo Finance (For stock market Data)
IDE : Jupyter Notebook , Vs Code