From 3e3a7ed2f54b29fad336ad06845bc24a21ee2e78 Mon Sep 17 00:00:00 2001
From: Piotr <pplonski86@gmail.com>
Date: Mon, 13 Jul 2020 14:59:28 +0200
Subject: [PATCH] Update README.md

---
 README.md | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/README.md b/README.md
index 2f5a83c5..b895cc18 100644
--- a/README.md
+++ b/README.md
@@ -48,6 +48,10 @@ 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. 
@@ -55,6 +59,10 @@ It is aimed to be used when the user wants to explain and understand the data.
 
 ### 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. 
@@ -62,6 +70,10 @@ It should be used when the user wants to train a model that will be used in real
 
 ### 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**.