Every engineering project has delays and issues, but machine-learning projects are harder to manage than any other. In the first week you might go from zero to 80% accuracy. The next 20% might take you another week, a month or a lifetime — it’s impossible to tell.
So how do you make an 80% accurate model useful? Until we’re replaced by robots, this is going to be the machine learning challenge of the next decade.
It is important to keep humans in the loop till then, that is, we need to get humans and computers to work together.
These days, we no longer need a Google-size R&D budget to make machine learning models developed and running for businesses and research settings. Even though the models aren’t perfect, they are still useful. If you are a machine learning/data science enthusiast, these technologies are definitely worth your attention.