Was ist Transfer Learning

Definition

Transfer Learning is a machine learning technique where a pre-trained model is repurposed and fine-tuned for a new, yet related task. This eliminates the need to train a model from scratch.

Explanation

By leveraging such pre-trained models, companies can drastically reduce the investment in computational power, time, and required training data. The model applies its acquired knowledge to a specific task, such as analyzing and classifying sales emails. In the SaaS and AI sectors, Transfer Learning thus empowers even smaller providers to offer highly precise AI solutions without massive development budgets. Through targeted fine-tuning based on proprietary B2B sales data, the system quickly adapts to the specific tonality and communication style of each company. This efficiency positions Transfer Learning as a key technology for modern, intelligent B2B software solutions.