scorpionhiccup/StockPricePrediction resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1537 stars · 437 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Jupyter Notebook-based research project applying supervised learning techniques (including LSTM/RNN models) to forecast stock prices from historical returns and Twitter sentiment indicators. It serves primarily as an educational reference with accompanying report, slides, and concept video.

Use cases

• predict stock prices with machine learning
• learn LSTM models for time-series forecasting
• build a stock price forecasting pipeline in Python
• incorporate Twitter sentiment into stock prediction
• compare regression models for financial forecasting
• study a supervised learning stock market project

When to choose

• learning how ML techniques apply to stock price forecasting
• studying an end-to-end forecasting pipeline with sentiment features
• referencing LSTM/RNN implementations for financial time series

When to avoid

• production trading systems needing reliable, maintained software
• real-time market data ingestion
• projects requiring active support or recent updates

Facets

learning-resource · maturity maintenance

machine-learning data-science nlp machine-learning fintech data-science time-series python stock-price-forecasting lstm rnn supervised-learning sentiment-analysis jupyter-notebook time-series-forecasting trading

Member repositories

For agents

markdown · JSON · MCP: product_card(name="scorpionhiccup/StockPricePrediction")