Python & AI/ML

# Python & AI/ML

import pandas as pd
import numpy as np

from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

data = pd.read_csv('data.csv')
X = data.drop('target', axis=1)
y = data['target']

X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42
)

model = RandomForestClassifier()
model.fit(X_train, y_train)

predictions = model.predict(X_test)

print('Model Accuracy:',
      model.score(X_test, y_test))