Summary
This chapter provided an overview of ML, deep learning, and the types of ML approaches. It also covered the ML life cycle and various ML use cases across different domains. We looked at a high-level overview of the TensorFlow Developer Certificate, along with information on the components of the exam and how to prepare for it. At the end of this chapter, you should have a good foundational understanding of what ML is and its types. You should now be able to determine which problems are ML-based problems and those that require classic programming. You should also be able to unpack ML problems into different types and be familiar with what it takes to prepare for the TensorFlow Developer Certificate exam by Google.
In the next chapter, we will look at what TensorFlow is, set up our environment, and start coding our way to the end of this book.