Software engineering for machine-learning applications: The road ahead
IEEE Software, 2018•ieeexplore.ieee.org
The First Symposium on Software Engineering for Machine Learning Applications (SEMLA)
aimed to create a space in which machine learning (ML) and software engineering (SE)
experts could come together to discuss challenges, new insights, and practical ideas
regarding the engineering of ML and AI-based systems. Key challenges discussed included
the accuracy of systems built using ML and AI models, the testing of those systems, industrial
applications of AI, and the rift between the ML and SE communities. This article is part of a …
aimed to create a space in which machine learning (ML) and software engineering (SE)
experts could come together to discuss challenges, new insights, and practical ideas
regarding the engineering of ML and AI-based systems. Key challenges discussed included
the accuracy of systems built using ML and AI models, the testing of those systems, industrial
applications of AI, and the rift between the ML and SE communities. This article is part of a …
The First Symposium on Software Engineering for Machine Learning Applications (SEMLA) aimed to create a space in which machine learning (ML) and software engineering (SE) experts could come together to discuss challenges, new insights, and practical ideas regarding the engineering of ML and AI-based systems. Key challenges discussed included the accuracy of systems built using ML and AI models, the testing of those systems, industrial applications of AI, and the rift between the ML and SE communities. This article is part of a theme issue on software engineering’s 50th anniversary.
ieeexplore.ieee.org
以上显示的是最相近的搜索结果。 查看全部搜索结果