3. ML

 from sklearn import datasets

from sklearn.model_selection import train_test_split

digits = datasets.load_digits()

X = digits.data

Y = digits.target

X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state=42)

from sklearn.svm import SVC

clf = SVC(kernel = 'linear', C=1)

clf.fit(X_train, Y_train)

from sklearn.metrics import accuracy_score 

y_pred = clf.predict(X_test)

accuracy = accuracy_score(Y_test, y_pred)

print(f"Accuracy: {accuracy * 100:.2f}%")