Game Theory

Game Theory is a mathematical framework used to study and analyse strategic decision-making in situations involving multiple actors or players. It helps businesses understand and predict the behaviour of competitors, customers, and other stakeholders. Game Theory finds applications in areas like pricing strategies, auction design, and negotiation tactics.

Generative Adversarial Networks (GANs)

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.

Generative Pre-trained Transformer (GPT)

GPT is an advanced language model that uses Deep Learning techniques to generate human-like text. Built on the Transformer architecture, GPT models have been trained on vast amounts of text data and can generate coherent and contextually relevant sentences. GPT has applications in natural language generation, chatbots, and content creation.

Genetic Algorithms

Genetic Algorithms are optimisation techniques inspired by the principles of evolution. By mimicking natural selection, Genetic Algorithms explore a large search space and find optimal solutions to complex problems, making them valuable tools for businesses in various domains.

Graph Neural Networks

Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform tasks such as node classification, link prediction, and graph generation. Graph Neural Networks are valuable for analysing social networks, biological networks, and recommendation systems.