Overview
Transfer learning is a powerful technique in deep learning where a model developed for one task is reused for another related task. This approach saves time and resources by leveraging existing knowledge. It is especially useful when there is limited data available for the new task. In this introduction, students will learn the basics of transfer learning and how it can enhance model performance in various applications.
📚 Key Learning Objectives
- ✓ Define transfer learning and its importance in deep learning.
- ✓ Identify scenarios where transfer learning is beneficial.
- ✓ Explain the process of transferring knowledge between tasks.
- ✓ Apply transfer learning techniques using popular frameworks.
- ✓ Evaluate the performance of models using transfer learning.
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