What is Transfer Learning?
What does 'Transfer Learning' mean?
Transfer learning is a powerful technique in artificial neural networks that allows a model to leverage knowledge gained from one task and apply it to another related task. Instead of training a model from scratch, which can be time-consuming and requires a lot of data, transfer learning uses pre-trained models that have already learned features from a large dataset. For example, a model trained on thousands of images to recognize general objects can be fine-tuned to identify specific types of objects, like dogs or cars, with a smaller dataset. This speeds up the training process and often leads to better performance because the model starts with a solid foundation of knowledge. Transfer learning is especially useful in fields like image recognition and natural language processing, where large amounts of data can be difficult to gather.
List of software with Transfer Learning functionality
About the reviewer
Rajat Gupta is the founder of Spotsaas. Over the past two years, he has reviewed 2,000+ tools across CRM, HR, AI, and finance — applying hands-on product research and a background in commerce and the CFA program to evaluate software through a business and ROI lens. His goal: help teams make software decisions they won't regret.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].