Summary

In this chapter, you learned the essence of the domain gap problem in ML. Additionally, you explored the main solutions to mitigate this problem. We focused on domain randomization in computer vision and NLP. Then, you learned about the main issues and limitations of synthetic-to-real domain adaptation. In the next chapter, we will explore and highlight diversity issues in synthetic data to better comprehend the pros and cons of synthetic data in ML.