Confusion Matrix
Confusion Matrix is a table showing correct and incorrect predictions per class to evaluate a classifier.
All
Computer Vision
Data
Deep Learning
Ethics
Fundamentals
Generative AI
Infrastructure
Machine Learning
NLP
Artificial Intelligence
Artificial Intelligence is the field of building computer systems that can perform tasks normally requiring human…
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.
Deep Learning
Deep Learning is a subset of machine learning that uses multi-layered neural networks to learn complex…
Dropout
Dropout is a regularisation method that randomly ignores some neurons during training to improve generalisation.
Neural Network
Neural Network is a model loosely inspired by the brain, made of layers of connected nodes…
Activation Function
Activation Function is a function applied to a neuron's output that lets neural networks model non-linear…
Large Language Model
Large Language Model is a neural network trained on huge amounts of text that can understand…
Softmax
Softmax is a function that turns a set of numbers into probabilities that sum to one,…
Generative AI
Generative AI is AI that creates new content — text, images, audio, video, or code —…
Vector
Vector is an ordered list of numbers that represents data in a form models can compute…
Natural Language Processing
Natural Language Processing is the area of AI focused on enabling computers to understand, interpret, and…
Weights
Weights is the learned parameters that determine how strongly inputs influence a neural network's output.
Computer Vision
Computer Vision is the field of AI that enables machines to interpret and understand visual information…
Bias Term
Bias Term is an extra learnable value added in a neuron that shifts the activation, helping…
Transformer
Transformer is a neural network architecture based on attention that powers most modern language and multimodal…
Overhead
Overhead is the extra compute, memory, or time an AI system needs beyond the core task.
Attention Mechanism
Attention Mechanism is a technique that lets a model weigh which parts of the input matter…
Edge AI
Edge AI is running AI models directly on local devices rather than in the cloud, for…
Prompt
Prompt is the instruction or input you give a generative AI model to tell it what…
Federated Learning
Federated Learning is training models across many devices without moving raw data off them, preserving privacy.
Prompt Engineering
Prompt Engineering is the practice of designing and refining prompts to get more accurate and useful…