Abstract
In recent years, machine learning (ML) has become a hot topic of research and application. ML model and huge amount of data growth difficulties still follow ML development. With the lack of new data and constant training, published ML models may soon become obsolete; unscrupulous data contributors may upload incorrectly labelled data, leading to poor training results; and data leakage and abuse are all possible outcomes. These issues can be effectively addressed by using blockchain, a new and rapidly evolving technology. With the advancement of various smart devices and the field of artificial intelligence and machine learning, interdisciplinary collaboration with blockchain technology may be incredibly valuable for future investigations. Collaborative ML and blockchain convergence can be studied here, with emphasis on how these two technologies can be combined and their application areas. On the other hand, look at the existing research’s shortcomings and future enhancements.
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Manimaran, A., Goundar, S., Chandramohan, D., Arulkumar, N. (2024). Application Areas, Benefits, and Research Challenges of Converging Blockchain and Machine Learning Techniques. In: Goundar, S., Anandan, R. (eds) Integrating Blockchain and Artificial Intelligence for Industry 4.0 Innovations. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-35751-0_1
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