diff --git a/Tutorials/intro_1.py b/Tutorials/intro_1.py
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+import pandas as pd 
+
+import matplotlib.pyplot as plt 
+
+from sklearn.datasets import load_iris 
+
+from sklearn.model_selection import train_test_split 
+
+from sklearn.ensemble import RandomForestClassifier 
+
+from sklearn.metrics import accuracy_score 
+
+ 
+
+# Load the Iris dataset 
+
+iris = load_iris() 
+
+data = pd.DataFrame(data=iris.data, columns=iris.feature_names) 
+
+target = pd.Series(data=iris.target) 
+
+ 
+
+# Data Exploration 
+
+print("Dataset Description:") 
+
+print(data.describe()) 
+
+ 
+
+# Data Visualization 
+
+data.plot(kind='box', subplots=True, layout=(2, 2), sharex=False, sharey=False) 
+
+plt.show() 
+
+ 
+
+# Train-test split 
+
+X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42) 
+
+ 
+
+# Train a Random Forest Classifier 
+
+rf_classifier = RandomForestClassifier(n_estimators=100, random_state=42) 
+
+rf_classifier.fit(X_train, y_train) 
+
+ 
+
+# Make predictions 
+
+y_pred = rf_classifier.predict(X_test) 
+
+ 
+
+# Calculate accuracy 
+
+accuracy = accuracy_score(y_test, y_pred) 
+
+print("Accuracy:", accuracy)