Rakesh9100/ML-Project-Drug-Review-Dataset

This is an innovative machine learning project that utilizes patient reviews with many other attributes to analyze and evaluate the effectiveness of drugs.

42
/ 100
Emerging

Combines NLP text vectorization (TfidfVectorizer) with structured feature engineering to transform patient reviews into predictive signals for drug ratings. The pipeline preprocesses temporal data, handles missing values via SimpleImputer, and encodes categorical attributes before training multiple scikit-learn classifiers for comparative performance evaluation. Built on the UCI Drug Review Dataset (Drugs.com), it leverages pandas, BeautifulSoup, and matplotlib for end-to-end data processing, modeling, and visualization.

102 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 9 / 25
Community 24 / 25

How are scores calculated?

Stars

102

Forks

121

Language

Python

License

Apache-2.0

Last pushed

Jan 02, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Rakesh9100/ML-Project-Drug-Review-Dataset"

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