import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer 
from sklearn import svm
from sklearn.metrics import classification_report, accuracy_score

df = pd.read_csv('/content/spam.csv', encoding='ISO-8859-1')
df.head()

vectorizer = CountVectorizer()
X = vectorizer.fit_transform(df['v2'])
y = df['v1']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)

model = svm.SVC (kernel='linear') 
model.fit(X_train, y_train)

predictions = model.predict(X_test)
print("Accuracy: ", accuracy_score (y_test, predictions)) 
print("Classification Report: ")
print(classification_report (y_test, predictions))