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

Deep Learning, a subfield of AI, leverages neural networks with numerous interconnected layers to process vast amounts of data, enabling machines to learn and…
Clustering in AI refers to the process of grouping similar data points together based on their inherent characteristics or attributes. By identifying patterns or…
Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make…
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…