Explaining what learned models predict
Explained what learned models predict
This essay was originally created for a university application. But before the essay gathers dust on my hard drive, Iād rather share it here š.
Abstract
There are many problems in computer science that cannot or can only be solved with extreme difficulty using pre-programmed rules. An example here would be the recognition and classification of images. Here, machine learning (ML) algorithms offer a good solution approach by recognizing regularities from previous examples, storing them, and applying them to the new images. However, the safety and reliability of machine-learning systems cannot be readily assessed because the individual steps in the learning process of an ML system are not easily comprehensible to a human, making the decision path very opaque. Given the ever-increasing impact of ML systems in our lives, it is very important that these systems are reliable since wrong or unintended results could have extreme consequences.
This paper will discuss a small sample of possible causes of reliability problems and present some solutions.