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

Decision Trees are Machine Learning models that use a branching structure to make decisions or predictions. By determining the most important features and creating…
One-Shot learning is an AI approach that enables models to learn from only one or a few examples. This approach is advantageous in tasks…
Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…
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…