Summary
In this chapter, we laid the foundation for understanding H2O machine learning at scale. We started by reviewing a bare minimum Hello World code example and discussed the problems of scale around it. Then, we introduced the H2O Core, Enterprise Steam, and MOJO technology components and how these can overcome problems of scale. Finally, we extracted a set of key concepts from these technologies to deepen our understanding.
In the next chapter, we will use this understanding to begin our journey of learning how to build and deploy world-class models at scale. Let the coding begin!
