Our goal is to develop a robust model capable of accurately predicting whether a given message is spam or not. We'll evaluate the models based on accuracy and precision metrics. Additionally, we'll test our model on real-world data to assess its performance.We'll employ various classifiers including SVC, MultinomialNB, DecisionTreeClassifier, LogisticRegression, RandomForestClassifier, AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, GradientBoostingClassifier, and XGBClassifier. to identify the spam emails

Data setis from from kaggle, here is the link https://www.kaggle.com/datasets/mfaisalqureshi/spam-email.