Update README.md

README.md

@@ -79,4 +79,40 @@ This function takes in the following arguments:
 
 * `data_file`: the path to the CSV file containing the data
 * `target_column`: the name of the column in the CSV file that contains the target variable
-```
+```
+
+Markdown rendered output : 
+
+
+User :
+Write a python function that trains a classifier on data loaded from a csv.
+GLaDOS :
+Here is an example of a function that trains a classifier on data loaded from a CSV file:
+
+```
+python
+import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.ensemble import RandomForestClassifier
+
+def train_classifier(data_file, target_column, test_size=0.2):
+    # Load the data from the CSV file
+    data = pd.read_csv(data_file)
+
+    # Split the data into training and testing sets
+    X_train, X_test, y_train, y_test = train_test_split(data.drop(target_column, axis=1),
+                                                        data[target_column],
+                                                        test_size=test_size)
+
+    # Train the classifier
+    clf = RandomForestClassifier()
+    clf.fit(X_train, y_train)
+
+    # Return the trained classifier and the test set predictions
+    return clf, clf.predict(X_test)
+
+```
+This function takes in the following arguments:
+
+* `data_file`: the path to the CSV file containing the data
+* `target_column`: the name of the column in the CSV file that contains the target variable