This is post #2 of a 2-part series focused on reinforcement learning, an AI deployment approach that is growing in popularity.
In this post I will provide a gentle introduction to reinforcement learning by way of its application to a classic problem: the multi-armed bandit problem.
We examine how to apply machine learning to segment based
on transaction data and transform those clusters into customer segments.
Utilizing AI techniques like NLP is a great way to reduce the time it takes to find optimal candidates for job openings.
Being able to accept machine learning outputs in the decision making process is critically important, especially in Air Traffic decisions.