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Ontologies for Business Analysis Udemy

#artificialintelligence

The practice of Business Analysis revolves around the formation, transformation and finalisation of requirements to recommend suitable solutions to support enterprise change programmes. Practitioners working in the field of business analysis apply a wide range of modelling tools to capture the various perspectives of the enterprise, for example, business process perspective, data flow perspective, functional perspective, static structure perspective, and more. These tools aid in decision support and are especially useful in the effort towards the transformation of a business into the "intelligent enterprise", in other words, one which is to some extent "self-describing" and able to adapt to organisational change. However, a fundamental piece remains missing from the puzzle. Achieving this capability requires us to think beyond the idea of simply using the current mainstream modelling tools.



Computational Neuroscience Coursera

@machinelearnbot

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.


Its Role Discourse Initiative: in Intelligent Tutoring Systems

AAAI Conferences

Over the past several years, researchers in natural language discourse have been grappling with the issue of discourse initiative. In the early days of natural language information systems, the user could ask questions or request advice and the system addressed the user's goals by providing the requested information. This has been characterized as a master-slave relationship(Grosz & Sidner 1990); in the case of natural language information systems, the user was the master and the system slavishly responded to the user's requests. Grosz and Sidner(Grosz & Sidner 1990) argued for a collaborative approach to discourse. More recently a number of researchers, including (Guinn 1996; Novick et al. 1996; Walker & Whittaker 1990; Whittaker & Stenton 1988), have investigated the issue of initiative in problem-solving discourse. However, relatively little attention has been given to the role of discourse initiative in intelligent tutoring systems. This paper argues that intelligent tutoring systems must allow for more discourse initiative on the part of the student. It presents several examples of discourse initiative that would be typical of training in a medical domain, proposes four hypotheses relating to discourse initiative in intelligent tutoring systems, and discusses some of the issues that must be addressed. Finally, it concludes with a brief description of our current research in this area.


Introduction to Computation and Programming Using Python - Programmer Books

#artificialintelligence

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts.