Artificial Intelligence for Business, 2nd Edition

16

Key Challenges

In this chapter:

• Getting a sufficient amount of quality data

• Avoiding the common mistake of mixing training data with test data

• Adopting a curious mindset

• Choosing the right tools

Given the potential of machine learning (ML), you can expect some challenges. In the previous chapter, we discussed one of the biggest challenges—deciding how to use a specific ML technique. Whether classification or clustering is best and whether supervised or unsupervised learning is most appropriate are not always clear-cut choices.

This chapter introduces you to other challenges you need to overcome—challenges that pose difficult questions, such ...