Summary
In this chapter, we introduced a novel and powerful method to generate synthetic data – using DMs. We compared DMs to other state-of-the-art generative models, and then, we highlighted the training process of DMs. Furthermore, we discussed the pros and cons of utilizing DMs. Additionally, we learned how to generate and utilize synthetic data in practice. We also examined the main ethical considerations usually raised when deploying DMs for synthetic data generation. You developed a comprehensive understanding of generative models, and you learned about standard DM architecture, the training process, and the main advantages, benefits, and limitations of utilizing DMs in practice. In the next chapter, we will shed light on several case studies, highlighting how synthetic data has been successfully utilized to improve computer vision solutions in practice. The chapter aims to inspire and motivate you to explore the potential of synthetic data in your own applications.
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