Deep Learning Research Review Week 2: Reinforcement Learning
This is the 2nd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on Reinforcement Learning.
Imagine you're blind folded in a rough terrain, and your objective is to reach the lowest altitude. One of the best and simplest strategies you can use, is to feel the ground in every direction, and take a step in the direction where the ground is descending the fastest. If you keep repeating this process, you might end up at the lake, or even better, somewhere in the huge valley.
The rough terrain is analogous to the cost function....
Machine learning is a field that threatens to both augment and undermine exactly what it means to be human, and it’s becoming increasingly important that you—yes, you—actually understand it.
I don’t think you should need to have a technical background to know what machine learning is or how it’s done. Too much of the discussion about this field is either too technical or too uninformed, and, through this blog, I hope to level the playing field.
This is for smart, ambitious people who want to know more about machine learning but who don’t care about the esoteric statistical and computational details underlying the field. You don’t need to know any math, statistics, or computer science to read and understand it.