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

Digital assistants, also known as Virtual Assistants or Chatbots, are AI-powered software applications that can engage in conversations and perform tasks on behalf of…
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…
Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…
Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…