Overview
A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed.
More in Machine Learning
SMOTE
Feature Engineering & SelectionSynthetic Minority Over-sampling Technique — a method for addressing class imbalance by generating synthetic examples of the minority class.
Hierarchical Clustering
Unsupervised LearningA clustering method that builds a tree-like hierarchy of clusters through successive merging or splitting of groups.
Content-Based Filtering
Unsupervised LearningA recommendation approach that suggests items similar to those a user has previously liked, based on item attributes.
Matrix Factorisation
Unsupervised LearningA technique that decomposes a matrix into constituent matrices, widely used in recommendation systems and dimensionality reduction.
Bandit Algorithm
Advanced MethodsAn online learning algorithm that balances exploration of new options with exploitation of known good options to maximise reward.
Backpropagation
Training TechniquesThe algorithm for computing gradients of the loss function with respect to network weights, enabling neural network training.
Model Registry
MLOps & ProductionA versioned catalogue of trained machine learning models with metadata, lineage, and approval workflows, enabling reproducible deployment and governance at enterprise scale.
Experiment Tracking
MLOps & ProductionThe systematic recording of machine learning experiment parameters, metrics, artifacts, and code versions to enable reproducibility and comparison across training runs.