Transfer Learning

Transfer learning is a machine learning technique in which a model trained on one task or dataset is reused and adapted for a related task. Instead of building a model from scratch, this approach leverages previously learned patterns, reducing the amount of data, time, and computational resources required. It is particularly effective when labeled data is limited in the target domain. Transfer learning enables faster development and improved performance by building on existing knowledge. In enterprise applications, transfer learning supports efficient deployment of AI solutions across similar use cases, improving scalability and accelerating time to value.