What is Transfer Learning?

Skill Level:

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

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used…
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…
Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…
Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new…