EN | HE
NET: ONLINE
XP: 0 | RANK: INITIATE
XP: 0 | RANK: INITIATE
DATA SCIENCE & AI
Dr. Igor Kleiner
WEEK 05
PROGRESS: 0 / 18
MODELING // LINEAR REGRESSION (WINE PRICES)
[ACTIVE SESSION]
SUMMARY // WHAT WE LEARNED
- 📈 Linear Regression: Drawing a line of best fit. Predicting continuous values like wine prices.
- 🍷 Features & Target: Using independent variables (features) to predict the dependent variable (target).
- 🎯 Evaluation Metrics: MAE, MSE, RMSE, and R². How we know if our model is any good or just guessing.
- ⚖️ Interpretation: Understanding coefficients and intercepts. Decoding the math behind the predictions.
CORE MATERIALS
BONUS MATERIALS