Just skimmed a public draft of the last chapter of Machine Learning Yearning book by Andrew Ng. I know a lot of people out there might be joking that it’s more like Machine Learning Yawning. But in reality, the execution of these seemingly simple ideas is probably incredibly difficult.

Consider the last time you put a multistage Machine Learning system into production where the output of one stage is the input of the next stage. Deciding to even try this is a monumentally difficult task. The data gathering, the training and verifications, the analysis required is so vast in it’s requirement, that most organization do not attempt it.

Luckily though, people are largely imperfect machines. This means we are usually equipped with ability to work around error prone components. One approach is discussion of a topic. The book’s accompanying discussion forum at deeplearning.ai seems like an effort to help everyone wrap our minds around this thing.

Cant wait to read more about it!