The /r/playrust Classifier...
summary
Built an end-to-end Rust classifier that detects /r/playrust posts on the Rust subreddit using Reddit API data, feature extraction implemented in typed Rust structs, parallelized with rayon parallelism, and a Random Forest model serialized for serving. Label encoding in Rust runs 15–20× faster than the pandas+scikit‑learn mirror and uses far less memory. The deployed model reports about 99% accuracy (≈98% true positive rate, <1% false positive rate). Visualization tooling is missing so exploration still uses Python.
AI-written summary · about
chapters (11)
- 0:00Start
- 2:58Service-Oriented Machine Learning
- 3:27Data Investigation
- 3:47Model Generation
- 9:30Try Macros
- 14:51Label Encoding
- 15:52Generate a Model and Perform Predictions
- 16:12State of the Rust Machine Learning Ecosystem
- 17:45Basic Code for Model Generation and Prediction
- 18:17Example Output
- 19:27Top Features
