If you are new to AI and Data Science and need quickly to get your head wrapped around the basic terms, this post is for you. Are you already experienced in the field, you might want not to spend your time with this post.
With the curtesy of Shehroz Aslam I became aware of a the Coursera course by Andrew Ng explaining the world of AI and Data Science in an easy-to-grasp fashion.
The aim here is to cherry-pick from Andrew Ng’s great insights.
Understanding the basic terms and their relation
The Sentinels in the Matrix or robots in The Terminator are stereotype and malign examples of Artificial General Intelligence (AGI). Only time will know if or when AGI could become a reality. In this post we’ll maintain contact with reality and “only” focus on Artificial Narrow Intelligence (ANI).
The top-level break-down of Artificial Intelligence as illustrated by Andrew Ng
It is decades, maybe hundreds or even thousand of years away before AGI can do what humans do Andrew Ng
Andrew Ng lists some well-known ANI applications e.g., self-driving car, smart speaker, web search, quality control in production etc.
Tools used to bring intelligence to computers
The universe of AI is rapidly branching. Here we’ll stick to the main branch as laid-out by Andrew Ng.
Andrew Ng provides some examples of open-source Machine Learning frameworks:
