JaideepGuntupalli/f1-predictor
🏎️ A machine-learning approach to predict Formula 1 Grand Prix race outcomes.
Combines historical F1 data from Ergast with feature engineering on driver nationality, circuit characteristics, and weather conditions to train ensemble classifiers (random forest, SVM, Naive Bayes, KNN) that predict podium finishes, points-scoring outcomes, and DNF probability. The Python backend (Pandas, scikit-learn) uses k-fold cross-validation for model selection, while a Next.js frontend with Tailwind CSS surfaces predictions through an interactive web interface.
No commits in the last 6 months.
Stars
74
Forks
15
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 28, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/JaideepGuntupalli/f1-predictor"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
Jared-Chan/f1ml
Formula One Race Lap-by-Lap Prediction with Machine Learning
VforVitorio/F1_Strat_Manager
AI Models for Strategy Recommendations in Formula 1 races. Final Thesys Project of UIE...
hugomagee/OptimalAthlete
ML system predicting 400m sprint times (R²=0.84) — trained on 18 months of personal race & training data
shameeh/F1-Predictive-Analytics-Architecture
This project ingests live Formula 1 telemetry, processes it through a highly scalable Medallion...
VaibhavSaran/F1-Primus-AI
An autonomous F1 race prediction agent that fetches weather, telemetry & news data before every...