Machine Learning, Data Science, AI, Deep Learning, and Statistics – It’s All So Confusing

It seems like these days every healthcare IT company out there is saying they’re doing machine learning, AI, deep learning, etc. So many companies are using these terms that they’ve started to lose meaning. The problem is that people are using these labels regardless of whether they really apply. Plus, we all have different definitions for these terms. As I search to understand the differences myself, I found this great tweet from Ronald van Loon that looks at this world and tries to better define it: Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics | #DataScience #MachineLearni … https://t.co/7PQRI2kfyN pic.twitter.com/v3wW3d19eB — Ronald van Loon (@Ronald_vanLoon) September 29, 2017 In that tweet, Ronald also links to an article that looks at some of the differences. I liked this part he took from Quora: AI (Artificial intelligence) is a subfield of computer science, that was created in the 1960s, and it was (is) concerned with solving tasks that are easy for humans, but hard for computers. In particular, a so-called Strong AI would be a system that can do anything a human can (perhaps without purely physical things). This is fairly generic, and includes all kinds of tasks, such as planning, moving around in the world, recognizing objects and sounds, speaking, translating, performing social or business transactions, creative work (making art or poetry), etc. NLP (Natural language processing) is simply the part of...
Source: EMR and HIPAA - Category: Information Technology Authors: Tags: Digital Health Healthcare Healthcare AI Healthcare Analytics HealthCare IT Deep Learning Healthcare Machine Learning NLP Ronald van Loon Source Type: blogs