import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split

# Load and prepare data
df = pd.read_csv('data.csv')
X = df.drop('target', axis=1)
y = df['target']

# Split the dataset
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.25, random_state=42
)

# Train machine learning model
from sklearn.ensemble import RandomForestClassifier
model = RandomForestClassifier()
model.fit(X_train, y_train)

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