Section outline

  • transfer learning

    • Transfer learning File

      In this chapter, the author discusses the fundamentals of transfer learning, starting with an overview of its basic concepts and formal definitions. Various strategies for implementing transfer learning are explored, alongside practical demonstrations to illustrate how these concepts work in real-world applications. The chapter also delves into the motivation behind using transfer learning and its advantages, particularly in scenarios with limited data availability. Additionally, the text provides a concise review of Convolutional Neural Networks (CNNs), which are often used in transfer learning tasks.