3 Preliminary research
This chapter covers
- Applying use cases from various domains to a given problem
- Facing and solving the “build-or-buy” dilemma in choosing a suitable solution
- Problem decompositioning
- Choosing the right degree of innovation
In chapter 2, we discovered that identifying a problem is the key element to developing a successful machine learning (ML) system. The better and more precisely you describe the problem, the higher the probability of building a product that will efficiently meet business goals.
Now we will delve into several key aspects that mark the next important stage of designing a comprehensive and efficient ML system—the solution space. This chapter will tell you more about finding solutions that helped solve similar problems in the past, the always tough choice between building our components and buying third-party products, a proper approach to decompositioning the problem, and picking the optimal degree of innovation, depending on the main objectives of our future system.
3.1 What problems can inspire you?
If I have seen further, it is by standing on the shoulders of Giants.