… systems that support machine learning are … systems and low-level primitives. In this work,
we present our vision for MLbase, a novel system harnessing the power of machine learning for …

… Many theoretical results in machine learning apply to all learning systems, whether they
are computer algorithms, animals, organizations, or natural evolution. As the field progresses, …

… for classifying and comparing learning systems, we turn to a brief historical outline of machine
learning. 14 CHAPTER 1 : AN OVERVIEW OF MACHINE LEARNING 1.4 AN HISTORICAL …

… A machine learning algorithm is a computational process … This training is the “learning”
part of machine learning. The … learning, only input samples are given to the learning system …

… sample, we can bound the probability that the learning system will produce an ^F with error
greater than . … We say that the learning system is probably approximately correct (PAC) if …

… Machine learning systems are both complex and unique. … holistic approach to designing
ML systems that are reliable, … of how it can help your system as a whole achieve its objectives. …

… machine learning systems. We present a taxonomy identifying and analyzing attacks against
machine learning systems. We … against machine learning systems and proposals for making …

… Abstract—In this paper, we propose a hybrid machine learning system based on Genetic …
The results show that the hybrid GA-SVM system outperforms the stand alone SVM system. …

… machine learning system that aims to reduce the burden on researchers undertaking systematic
reviews. A system… ) to interact with the machine learning system. More specifically, the …

… a machine learning approach. In this paper, we compare the performance of a neural network
(NN), a support vector machine, a system … ” suitable for machine learning during his or her …