data-sci-portfolios
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: mcnabb998
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 32.2 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Stars vs Sentiment Portfolio
Explore how star ratings compare with written sentiment using open datasets.
A collection of mini-projects showcasing reproducible analyses of review data. Each folder under projects/ contains notebooks, a Makefile, and result images.
The docs/ directory powers a simple GitHub Pages site that links out to individual portfolio pieces.
New in Milestone 2: dedicated About and Contact pages plus a refreshed landing page.
Highlights - 📊 Reproducible notebooks - 🖼️ Result images and charts - 🌐 Simple GitHub Pages site
Table of Contents
Projects
- London Underground Upgrade Impact Analysis – Causal impact of infrastructure upgrades on LU reliability, ridership, and outcomes (2010–2024)
- Amazon “Stars vs Sentiment” Review Analysis – Measuring divergence between star ratings and textual sentiment using one million reviews
- FEMA Flood Insurance Claim Prediction – Predicting claim probability from flood zone, elevation and construction data
- Real Estate COVID WFH Features – Quantifying price and speed effects of remote‑work amenities in real estate listings
- NYC Taxi Trip Duration Prediction – Modeling taxi trip times with engineered spatial and temporal features
- Movie Review Sentiment Classification – Building and comparing NLP pipelines for classifying movie review sentiment
- Airbnb Price Predictor – Explaining nightly price variation for New York City Airbnb listings
- Stock Price Trend Forecasting – Comparing ARIMA, Prophet and LSTM models for short‑term stock forecasts
- Traffic Accident Hotspot Detection – Identifying high‑risk intersections using clustering and mapping
- Disease Diagnosis from Symptoms – Demonstrating symptom encoding and classification for multi‑label diagnosis
Quickstart
bash
cd projects/amazon-stars-vs-sentiment
conda env create -f environment.yml
conda activate stars-sentiment
make all
For details of each step, see the notebooks directory.
Citation
If you use these materials, please cite the repository using the CITATION.cff file.
Owner
- Name: Matthew McNabb
- Login: mcnabb998
- Kind: user
- Location: San Antonio
- Repositories: 1
- Profile: https://github.com/mcnabb998
Citation (CITATION.cff)
---
cff-version: 1.2.0
title: "Stars vs Sentiment Portfolio"
authors:
- family-names: McNabb
given-names: Matthew
orcid: "https://orcid.org/0000-0000-0000-0000"
version: "0.1.0"
URL: "https://github.com/mcnabb998/Data-Sci-Portfolios"
message: "If you use this work, please cite it as below."
year: 2024
GitHub Events
Total
- Delete event: 31
- Push event: 92
- Pull request review comment event: 9
- Pull request review event: 5
- Pull request event: 61
- Create event: 34
Last Year
- Delete event: 31
- Push event: 92
- Pull request review comment event: 9
- Pull request review event: 5
- Pull request event: 61
- Create event: 34
Dependencies
- actions/checkout v4 composite
- actions/configure-pages v5 composite
- actions/deploy-pages v4 composite
- actions/upload-pages-artifact v3 composite
- sentence_transformers *
- black ==24.4.2 development
- flake8 ==7.0.0 development
- mypy ==1.10.0 development
- pre-commit ==3.7.1 development
- pytest ==8.2.0 development
- pytest-cov ==5.0.0 development