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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

Big Data

Big Data refers to large, complex datasets that cannot be easily managed or analysed with traditional data processing methods. AI techniques, such as Machine…

Human-in-the-Loop

Human-in-the-loop refers to a collaborative approach where humans and AI systems work together to achieve optimal results. It involves combining human expertise, judgement, and…

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…

Supervised Learning

Supervised Learning is a Machine Learning approach where models are trained using labelled data, with both input and output pairs. By learning from the…
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