Machine Learning dengan Python

Machine Learning adalah cabang AI yang memungkinkan komputer belajar dari data tanpa diprogram secara eksplisit.

Jenis-Jenis Machine Learning

1. Supervised Learning — Data memiliki label target (contoh: Prediksi harga rumah, klasifikasi email spam).

2. Unsupervised Learning — Data tidak memiliki label (contoh: Segmentasi pelanggan dengan K-Means Clustering).

3. Reinforcement Learning — Belajar melalui reward & penalty (contoh: AI Catur, mobil otonom).

Contoh Script Model Klasifikasi dengan Scikit-Learn:

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

# 1. Load Dataset
data = pd.read_csv('user_activity.csv')
X = data[['study_hours', 'quiz_score', 'streak_days']] # Features
y = data['passed_exam']                                 # Target Label

# 2. Split Data (80% Train, 20% Test)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 3. Inisialisasi & Latih Model ML
model = RandomForestClassifier(n_estimators=100)
model.fit(X_train, y_train)

# 4. Evaluasi Akurasi
predictions = model.predict(X_test)
accuracy = accuracy_score(y_test, predictions)
print(f"🎯 Akurasi Model Machine Learning: {accuracy * 100:.2f}%")