Discussion

Abstract

At the end of a tour from curve fitting to machine learning there are two kinds of questions that usually remain: The first kind is about the numerous details and side branches of the sketched topics that had to be omitted for the sake of readability and comprehensibility -limitations are inevitable and a bunch of important and interesting issues had to be skipped. The second kind of questions addresses the more abstract and general aspects that arise from the earlier discussions like the principal capabilities of machine learning. In this final chapter some so far neglected topics that belong to both kinds of questions are outlined.

First a crucial aspect of computation is discussed: Speed. A proper estimate of the time period necessary to perform a computational task is essential for almost all practical applications (section 5.1). After an initial fascination a deeper insight into machine learning often leads to a notion of disappointment about what can be expected from these methods in principal thus some basic possibilities and limits are discussed (section 5.2). The relations of the methods outlined on the road from curve fitting to machine learning to a possibly emerging computational intelligence are of general interest and thus briefly sketched (section 5.3). Final remarks close this chapter (section 5.4).