# scorpionhiccup/StockPricePrediction

Stock Price Prediction using Machine Learning Techniques

Repository: https://github.com/scorpionhiccup/StockPricePrediction
Canonical: https://ross.abutalabs.com/products/stockpriceprediction
Homepage: http://scorpionhiccup.github.io/StockPricePrediction
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: machine-learning, supervised-learning, stock-price-forecasting, forecasting, rnn, lstm, lstm-neural-networks, video, concept-video, analysis
Last push: 2023-08-08T03:17:09+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3836, "days_push": 1121, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1537, forks 437 (observed 2026-08-28T04:05:00.158375+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, nlp
- domain: machine-learning, fintech, data-science, time-series
- platform: python
- tags: stock-price-forecasting, lstm, rnn, supervised-learning, sentiment-analysis, jupyter-notebook, time-series-forecasting, trading

## Member repositories
- scorpionhiccup/StockPricePrediction (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:00.158375+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:31:01.965948+00:00, confidence not recorded.
  - readme: https://github.com/scorpionhiccup/StockPricePrediction (fetched 2026-08-28T04:05:00.158375+00:00, sha 0345e2156221)
  - homepage: http://scorpionhiccup.github.io/StockPricePrediction (fetched 2026-08-29T11:32:52.983944+00:00, sha a78bf3718068)
- Data as of 2026-08-30T08:39:29.467469+00:00.