pages/5_Modeling.py

import streamlit as st
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score

def run():
    st.title("4. Modeling")
    st.write("## Overview")
    st.write("Building and training machine learning models to make predictions.")

    st.write("## Key Concepts & Explanations")
    st.markdown("""
    - **Model Selection**: Choose the model based on the problem (e.g., Classification, Regression).  
    - **Training Data**: The subset used to train the model.  
    - **Test Data**: The subset used to evaluate the model’s performance.
    """)

    file = st.file_uploader("Upload a dataset for modeling", type=["csv"])
    if file:
        df = pd.read_csv(file)
        target = st.selectbox("Select the target variable", df.columns)
        features = st.multiselect("Select the feature columns", df.columns)

        if target and features:
            X = df[features]
            y = df[target]
            X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

            model = LogisticRegression()
            model.fit(X_train, y_train)
            y_pred = model.predict(X_test)
            accuracy = accuracy_score(y_test, y_pred)

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

    st.write("## Quiz: Conceptual Questions")
    q1 = st.radio("What is overfitting?", ["Model too simple", "Model too complex", "Data too large"])
    if q1 == "Model too complex":
        st.success("✅ Correct!")
    else:
        st.error("❌ Incorrect.")

    st.write("## Code-Based Quiz")
    code_input = st.text_area("Write a function to split data into train and test sets", value="def split_data(df, target):\n    X = df.drop(columns=[target])\n    y = df[target]\n    return train_test_split(X, y, test_size=0.2, random_state=42)")
    if "train_test_split" in code_input:
        st.success("✅ Correct!")
    else:
        st.error("❌ Try again.")

    st.write("## Learning Resources")
    st.markdown("""
    - 📖 [Introduction to Machine Learning with Python](https://www.oreilly.com/library/view/introduction-to-machine/9781449369880/)
    """)