Summary

In this chapter, we covered topics surrounding AI services. We went over a list of AWS AI services and where they can be used to build ML solutions. We also talked about adopting MLOps for AI services deployment. Now, you should have a good understanding of what AI services are and know that you don't need to always build custom models to solve ML problems. AI services provide you with a quick way to build AI-enabled applications when they are a good fit.

Hopefully, this book has provided you with a good view of what the ML solutions architecture is and how to apply the various data science knowledge and ML skills to the different ML tasks at hand, such as building an ML platform. It is exciting to be an ML solutions architect now, as you have a broad view of the ML landscape to help different organizations drive digital and business transformation across different industries.

So, what's next? AI/ML is a broad field with many sub-domains, so developing technical...