Update README.md

README.md

@@ -48,20 +48,32 @@ It integrates many popular frameworks:
 
 ### Explain 
 
+```py
+automl = AutoML(mode="Explain")
+```
+
 It is aimed to be used when the user wants to explain and understand the data.
  - It is using 75%/25% train/test split. 
  - It is using: `Baseline`, `Linear`, `Decision Tree`, `Random Forest`, `Xgboost`, `Neural Network` algorithms and ensemble. 
  - It has full explanations: learning curves, importance plots, and SHAP plots.
 
 ### Perform
 
+```py
+automl = AutoML(mode="Perform")
+```
+
 It should be used when the user wants to train a model that will be used in real-life use cases.
  - It is using 5-fold CV.
  - It is using: `Linear`, `Random Forest`, `LightGBM`, `Xgboost`, `CatBoost` and `Neural Network`. It uses ensembling. 
  - It has learning curves and importance plots in reports.
 
 ### Compete
 
+```py
+automl = AutoML(mode="Compete")
+```
+
 It should be used for machine learning competitions.
  - It is using 10-fold CV. 
  - It is using: `Linear`, `Decision Tree`, `Random Forest`, `Extra Trees`, `LightGBM`, `Xgboost`, `CatBoost`, `Neural Network` and `Nearest Neighbors`. It uses ensemble and **stacking**.