Machine Learning, Unsupervised Learning, Data Science, Artificial Intelligence, Clustering.
reduce the number of variables such that models can be trained with as much relevant information as possible, while removing the influence of noise that can be posed by having too many features to train on. 3. Anomaly Detection: Although anomaly detection can be both supervised and unsupervised,