Yeah, as most people here wrote already, it's statistics. And your models will yield those statistics... Unfortunately if you're an engineer/physicist/chemist/

Yeah, as most people here wrote already, it's statistics. And your models will yield those statistics... Unfortunately if you're an engineer/physicist/chemist/biologist/social-scientist your background in statistics is neither fresh nor deep. So your professor comes to you: can you do something with ML, it's such a hot topic (your boss has also no background in statistics nor do his peers (which review your stuff...)) you say: yes (because a no I don't know about it won't be good for you). Then you go to some google or blockchain sponsored-tutorial where some self-taught-Indian-CS-Bachelor is telling you how to use ML with Python and Tensorflow. You might wonder about some things but in the end you need to get things done and feed your data (which is often garbage, but verifying that it's not is not hot) into an algorithm you don't understand. Then you find some other guys, doing this, cite them and publish. 0 scientific value generated, but a great step for your academic carrer nonetheless.