What is Machine Learning?

Machine Learning (ML) is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed.

Types of Machine Learning

  1. Supervised Learning — learns from labeled data
  2. Unsupervised Learning — finds patterns in unlabeled data
  3. Reinforcement Learning — learns through trial and error

A Simple Example with scikit-learn

Here is a basic classification example:


from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

# Load data
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(
    iris.data, iris.target, test_size=0.2, random_state=42
)

# Train model
clf = RandomForestClassifier(n_estimators=100)
clf.fit(X_train, y_train)

# Evaluate
predictions = clf.predict(X_test)
print(f"Accuracy: {accuracy_score(y_test, predictions):.2f}")

Popular Python ML Libraries

  • scikit-learn — general-purpose ML
  • TensorFlow — deep learning framework by Google
  • PyTorch — deep learning framework by Meta
  • pandas — data manipulation and analysis

Visit scikit-learn.org to get started.