AML Study Guide 2026

K-Means Clustering is a prominent unsupervised learning technique used for partitioning a dataset into K distinct, non-overlapping subgroups or clusters. Unlike supervised methods, it does not require pre-labeled data; instead, it identifies inherent groupings based on the similarity of data points. This makes it ideal for tasks like customer segmentation or anomaly detection where labels are unknown.

The goal of data governance is to establish and enforce policies, procedures, and standards for managing an organization's data assets. This ensures data integrity, quality, security, and compliance with relevant regulations and ethical guidelines. Effective data governance is essential for reliable AI systems, as it guarantees that the data used for training and operation is trustworthy and legally sound.

Monitoring live prediction confidence and accuracy reveals model drift and performance degradation before it significantly impacts business outcomes.

Evidence-based practice combines rigorous research evidence, professional clinical expertise, and client/patient preferences and values to make informed decisions that optimize outcomes.

A stochastic policy maps each state to a probability distribution over actions, enabling exploration by sampling from this distribution during training.

NER tags spans of text that refer to specific entities like person names, companies, dates, and geographic locations.