House Price Prediction

Kaggle Datasets (over 80 features!)

A lot of feature engineering before the training and predicting:

• manual feature selection
• data types handling (assigning either categorical or numerical values)
• missing values analysis and replacing
• backward elimination of features
• feature scaling

Training and tuning ML regression algorithms:

• Logistic Regression
• Decision Tree
• Random Forest
• XGBoost
• Gradient Boosting