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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