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What is Transfer Learning?

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Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models on large datasets, businesses can save time and resources in training new models and achieve better performance in areas like natural language processing, image recognition, and recommendation systems.

Other Definitions

Probabilistic Graphical Models

Probabilistic Graphical Models is a type of statistical model used in Machine Learning and Artificial Intelligence. They represent complex relationships between variables through graphs…

Federated Learning

Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…

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…

ChatGPT

ChatGPT is an AI model developed by OpenAI that excels in generating human-like text-based responses. Powered by advanced language models and deep learning techniques,…
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