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omerluski/
winter-olympics-age-predictor

Name: winter-olympics-age-predictor
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Olympic Games ML Project - Presentation

לחצו על התמונה למעלה כדי לצפות בסרטון ההצגה של הפרויקט.

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

omerluski/winter-olympics-age-predictor