Regression

Root Mean Squared Error

80%–20%

train_test_split()

0 to 1

StandardScaler

Actual negative predicted as negative

Considers total true positives, false positives, and false negatives

accuracy_score

Gradient Boosting

Kaggle, AWS datasets, UCI Machine Learning Repository

Data loading, Data visualization, Model fine-tuning

Supervised learning, Unsupervised learning, Dimensionality reduction

dropna(), fillna()

Features, Response