Classification
Identifying which category an object belongs to.
Applications: Spam detection, image recognition. Algorithms: Gradient boosting, nearest neighbors, random forest, logistic regression, and more...
Regression
Predicting a continuous-valued attribute associated with an object.
Applications: Drug response, stock prices. Algorithms: Gradient boosting, nearest neighbors, random forest, ridge, and more...
Clustering
Automatic grouping of similar objects into sets.
Applications: Customer segmentation, grouping experiment outcomes. Algorithms: k-Means, HDBSCAN, hierarchical clustering, and more...
Dimensionality reduction
Reducing the number of random variables to consider.
Applications: Visualization, increased efficiency. Algorithms: PCA, feature selection, non-negative matrix factorization, and more...
Model selection
Comparing, validating and choosing parameters and models.
Applications: Improved accuracy via parameter tuning. Algorithms: Grid search, cross validation, metrics, and more...
Preprocessing
Feature extraction and normalization.
Applications: Transforming input data such as text for use with machine learning algorithms. Algorithms: Preprocessing, feature extraction, and more...
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