首页|Reports from Polytechnique Montreal Advance Knowledge in Software Engineering (B uilding Domain-Specific Machine Learning Workflows: A Conceptual Framework for t he State of the Practice)
Reports from Polytechnique Montreal Advance Knowledge in Software Engineering (B uilding Domain-Specific Machine Learning Workflows: A Conceptual Framework for t he State of the Practice)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on software engineering i s the subject of a new report. According to news reporting out of Montreal, Cana da, by NewsRx editors, research stated, “Domain experts are increasingly employi ng machine learning to solve their domain-specific problems.” The news journalists obtained a quote from the research from Polytechnique Montr eal: “This article presents to software engineering researchers the six key chal lenges that a domain expert faces in addressing their problem with a computation al workflow, and the underlying executable implementation. These challenges aris e out of our conceptual framework which presents the “route” of transformations that a domain expert may choose to take while developing their solution. To grou nd our conceptual framework in the state of the practice, this article discusses a selection of available textual and graphical workflow systems and their suppo rt for the transformations described in our framework. Example studies from the literature in various domains are also examined to highlight the tools used by t he domain experts as well as a classification of the domain specificity and mach ine learning usage of their problem, workflow, and implementation.”
Polytechnique MontrealMontrealCanadaNorth and Central AmericaCyborgsEmerging TechnologiesEngineeringMachin e LearningSoftware Engineering
NETL
NSTL
