EMAIL-SPAM-CLASSIFIER by @Rohan Singh

This is a project I made to classify spam emails

import pandas as pd from sklearn.model_selection import train_test_split from sklearn.feature_extraction.text import CountVectorizer from sklearn.naive_bayes import MultinomialNB import streamlit as st

Load data

data = pd.read_csv(r"C:/Users/rohan/Downloads/archive/spam.csv", encoding='latin-1')

Clean data

data = data[['v1','v2']] data.columns = ['Category','Message'] data.drop_duplicates(inplace=True) data['Category'] = data['Category'].replace(['ham','spam'], ['Not Spam','Spam'])

Split

X = data['Message'] y = data['Category']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

Vectorize

cv = CountVectorizer(stop_words='english') X_train_vec = cv.fit_transform(X_train)

Model

model = MultinomialNB() model.fit(X_train_vec, y_train)

Predict

def predict(message): message_vec = cv.transform([message]) return model.predict(message_vec)[0]

================= UI =================

st.title('📩 Spam Message Detector')

input_msg = st.text_input('Enter message here:')

if st.button('Validate'): if input_msg.strip() != "": output = predict(input_msg)

    if output == "Spam":
        st.error(f"🚨 {output}")
    else:
        st.success(f"✅ {output}")
else:
    st.warning("Please enter a message")