omerluski/winter-olympics-age-predictor

Olympic Games ML Project - Presentation

לחצו על התמונה למעלה כדי לצפות בסרטון ההצגה של הפרויקט.

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Winter Olympics Age Predictor

Project Overview

Predicting the age of Winter Olympic athletes based on physical characteristics (height, weight, BMI) and sport type.

Dataset: 120 Years of Olympic History (Winter subset)
Target: Athlete Age (Regression + Classification)
Best RMSE: 3.27 (Random Forest with Hyperparameter Tuning)

Models

Model	Type	RMSE / Accuracy
Linear Regression	Regression (baseline)	~5.X
Decision Tree	Regression	~X.XX
Random Forest	Regression (winner)	3.27
Logistic Regression	Classification	~XX%
KNN	Classification	~XX%
Random Forest	Classification (winner)	~XX%

Key Findings

• BMI is the strongest predictor of athlete age
• Sport type significantly affects age distribution
• Random Forest outperforms linear models on this dataset

Files

• olympic_model.pkl — Regression model
• olympic_classifier.pkl — Classification model
• notebook.ipynb — Full analysis

Video Presentation

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