shauryya28/tcs_stock_price_prediction

Financial time-series modeling of TCS stock using feature engineering (OHLC, moving averages, lag features) and ML/DL models including Linear Regression, XGBoost, and LSTM. Achieved R² = 0.99994, demonstrating data-driven model selection over complexity.

14
/ 100
Experimental
No License No Package No Dependents
Maintenance 13 / 25
Adoption 0 / 25
Maturity 1 / 25
Community 0 / 25

How are scores calculated?

Stars

Forks

Language

Jupyter Notebook

License

Last pushed

Mar 15, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shauryya28/tcs_stock_price_prediction"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.