Features

Data Preparation: Used YFinance API to fetch stock data for Apple, Microsoft, IBM, Johnson & Johnson, and General Electric.

Preprocessing: Cleaned and structured stock datasets for consistent analysis.

Technical Indicators: Implemented EMA (Exponential Moving Average) SMA (Simple Moving Average) RSI (Relative Strength Index) VWAP (Volume-Weighted Average Price)

EDA: Extracted trends and visualized historical stock patterns (2005–2025).

Forecasting Models: Built and compared LSTM, ARIMA, SARIMA, and Facebook Prophet models for both short-term and long-term predictions.

Demonstrations: Built an interactive dashboard using Streamlit.

Tech stack

Languages & Libraries: Python 3, Pandas, NumPy, TA-Lib

Visualization: Matplotlib, Seaborn, Plotly, Power BI

Machine Learning & Forecasting: Scikit-learn, Statsmodels, TensorFlow, Keras

Deployment & BI: Streamlit, Power BI

Demonstrations

LSTM

PROPHET

ARIMA

SARIMA