Summary
In this chapter, you gained a high-level understanding of recent advancements in machine learning modeling beyond supervised learning, including generative modeling, reinforcement learning, and self-supervised learning. You also learned about optimal prompting and prompt engineering to benefit from tools and applications built on top of generative models that accept text prompts as input from users. You were provided with the relevant code repositories and functionalities available in Python and PyTorch that will help you to start learning more about these advanced techniques. This knowledge helps you not only better understand how they work if you come across them but also start building models of your own using these advanced techniques.
In the next chapter, you will learn about the benefits of identifying causal relationships in machine learning modeling and practice with Python libraries that help you in implementing causal modeling.
