Too many features dragging you down? Try PCA or RecursiveFeatureElimination.
Classification
Predicting which category an observation belongs to
Regression
Predicting continuous outcomes
Clustering
Grouping similar data points together.
Dimension Reduction
Reducing dimensionality while minimising information loss
Feature Engineering
Reducing the number of features or combining them in new ways
Outlier Detection
Identifying anomalies or outliers in the data
Class Imbalance
Handling imbalance in dataset labels with resampling
Missing Value Imputation
Filling in missing data points in a dataset
Text Analysis
Extracting insights or patterns from textual data
Image Processing
Analyzing and manipulating visual data
Density Estimation
Models that learn a probability distribution from data