Confusion Matrix
Confusion Matrix is a table showing correct and incorrect predictions per class to evaluate a classifier.
Cross-Validation
Cross-Validation is a method of testing a model on multiple data splits to estimate how well…
Machine Learning
Machine Learning is a branch of AI where systems learn patterns from data and improve at…
Regularization
Regularization is techniques that discourage overly complex models to reduce overfitting.
Benchmark
Benchmark is a standard dataset and metric used to compare the performance of different models.
Fine-Tuning
Fine-Tuning is further training a pre-trained model on a specific dataset so it performs better on…
Pre-training
Pre-training is the initial, large-scale training of a model on broad data before it is adapted…
Transfer Learning
Transfer Learning is reusing a model trained on one task as the starting point for a…
Supervised Learning
Supervised Learning is training a model on labelled examples so it learns to map inputs to…
Unsupervised Learning
Unsupervised Learning is training a model to find structure or patterns in data that has no…
Reinforcement Learning
Reinforcement Learning is training an agent to make decisions by rewarding good actions and penalising bad…
Catastrophic Forgetting
Catastrophic Forgetting is when a model trained on new data loses what it previously learned.
Overfitting
Overfitting is when a model learns the training data too closely, including its noise, and performs…
Active Learning
Active Learning is a strategy where the model chooses the most useful examples for humans to…
Underfitting
Underfitting is when a model is too simple to capture the underlying pattern in the data…
Self-Supervised Learning
Self-Supervised Learning is learning from unlabelled data by creating its own training signals, key to modern…
Feature
Feature is an individual measurable property of the data that a model uses to make predictions.
Feature Engineering
Feature Engineering is the process of selecting and transforming raw data into features that improve model…
Hyperparameter
Hyperparameter is a configuration set before training — like learning rate or batch size — that…
Anomaly Detection
Anomaly Detection is identifying data points that differ significantly from the norm, often used for fraud…
Clustering
Clustering is grouping similar data points together without predefined labels.
Classification
Classification is assigning input data to one of several predefined categories.
Regression
Regression is predicting a continuous numeric value, such as a price or temperature.
Decision Tree
Decision Tree is a model that makes predictions by following a branching series of yes/no questions.