scikit-learn is the most widely used Python ML library — consistent API, excellent documentation, and implementations of virtually every classical ML algorithm.

Core scikit-learn API Pattern

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

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

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

predictions = model.predict(X_test)
print(classification_report(y_test, predictions))

Key Modules

• sklearn.model_selection — cross-validation, hyperparameter tuning
• sklearn.preprocessing — scaling, encoding
• sklearn.pipeline — chain preprocessing and modeling

Reference:

scikit-learn documentation

https://scikit-learn.org/stable/