Transfer Machine Learning Algorithms

In this chapter we explore and understand the concept of transfer machine learning algorithms, which deals with the ability to utilize the existing knowledge and transfer it to a specific target task effectively and efficiently. We perceive the scope, significance and various types of transfer learning and traverse through its emergence along with some prevailing applications in recent times. This chapter also includes several benefits and popular techniques of transfer learning that are prevalent. Transfer Learning methods have already been successfully applied to various domains and applications, we strive to comprehend its utilization in different applications using numerous use case solutions. We also uncover the associated challenges and limitations of transfer learning in order to make use of it in the best possible way. The usage of transfer learning is well-known to boost the algorithm performance, and we discuss its applicability more in the future direction to research. We conclude our chapter by summarizing what we have learned so far with some main key takeaways in order to use transfer learning in real-world applications.