In this chapter, we learned about the ML services offered by GCP. We started with the theory of ML to introduce basic concepts and nomenclature so as to better understand the actual services. We learned that, depending on your role and use case, you need to make the correct choice as to which service will be the most effective for you to use. One goal can sometimes be achieved using two or more different services. We also learned that you don't need to be a data scientist to leverage ML. Those of you who have very limited knowledge can use pretrained models. If those models are not good enough for your use case, you can try AutoML, which allows new models to be created without us having to develop the model ourselves. We just need to deliver proper datasets to GCP.
Finally, for those of you who have the knowledge, and are capable of developing your own models, ML...
