Deep Learning

Artificial Intelligence

Artificial Intelligence (AI) is the field of computer science concerned with building systems that perform tasks normally requiring human intelligence, such as…

Generative AI

Generative AI refers to models that create new content — text, images, audio, video, or code — rather than only classifying or predicting labels for existing d…

Machine Learning

Machine Learning (ML) is a subfield of AI in which systems improve their performance on a task by learning patterns from data, rather than following explicitly…

Deep Learning

Deep Learning is a subset of machine learning that uses artificial neural networks with many layers ('deep' architectures) to automatically learn hierarchical…

Neural Network

A neural network is a computational model composed of interconnected layers of simple processing units called neurons, loosely inspired by biological brains. E…

LLM

A Large Language Model (LLM) is a neural network, typically based on the transformer architecture, trained on massive amounts of text to predict and generate h…

Inference

Inference is the process of running a trained machine learning model on new input data to produce a prediction, classification, or generated output. It is dist…

LoRA

LoRA (Low-Rank Adaptation) is a parameter-efficient fine-tuning technique that adapts a large pretrained model by freezing its original weights and injecting s…

Mixtral

Mixtral is a family of open-weight large language models from Mistral AI built on a sparse mixture-of-experts (MoE) architecture, which activates only a subset…

MuZero

MuZero is a reinforcement learning algorithm from Google DeepMind, introduced in 2019, that learns to master games and planning tasks — including chess, shogi,…

YOLO

YOLO (You Only Look Once) is a family of real-time object detection models, originally introduced by Joseph Redmon in 2016, that detect and classify multiple o…

ResNet

ResNet (Residual Network) is a convolutional neural network architecture introduced by Microsoft Research in 2015 that uses "skip connections" to let very deep…

GAN

A Generative Adversarial Network (GAN) is a machine learning framework, introduced by Ian Goodfellow and colleagues in 2014, in which two neural networks — a g…

Variational Autoencoder (VAE)

A Variational Autoencoder (VAE) is a generative neural network architecture, introduced by Diederik Kingma and Max Welling in 2013, that learns to compress dat…

Mixture of Experts (MoE)

Mixture of Experts (MoE) is a neural network architecture design in which a model is composed of many specialized sub-networks ("experts"), with a learned rout…

Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI) refers to a hypothetical form of AI that can understand, learn, and apply knowledge across a wide range of tasks at a lev…

Neural Architecture Search

Neural Architecture Search (NAS) is an automated technique for designing effective neural network architectures by systematically searching a space of possible…

GPU Computing

GPU computing is the use of a graphics processing unit's highly parallel architecture to accelerate general-purpose computation, not just rendering graphics, b…

Natural Language Processing (NLP)

Natural Language Processing (NLP) is the field of artificial intelligence focused on enabling computers to understand, interpret, generate, and interact using…

Machine Learning vs Deep Learning vs AI Explained

A comprehensive guide to machine learning vs deep learning vs ai explained — written for learners at every level.

Neural Networks Explained with Simple Analogies

Neural networks are webs of simple units trained to recognise patterns — explained here without any maths.