… Software Engineering for Machine Learning Applications (SEMLA) aimed to create a space
in which machine learning (ML) and software engineering (… regarding the engineering of ML …

… to clarify the software engineering challenges for machine learning applications that either
exist … to knowledge areas defined by the Software Engineering Body of Knowledge (Swebok). …

… describe the road ahead for the above-mentioned requirements toward making AI4SE tools
… how AI – including data mining, machine learning, information retrieval, natural language …

… regular software applications) since modules in machine learning … that ML applications are
structurally different from applications in … : The road ahead,” IEEE Software, vol. 35, no. 5, pp. …

… Then we assess each software development process … Finally we discuss the application of
this adapted and … This is a “decision gate” for moving ahead with development using ML. The …

… describe the road ahead for the above-mentioned requirements toward making AI4SE tools
… how AI – including data mining, machine learning, information retrieval, natural language …

… The increasing reliance on applications with machine learning (ML) components calls for
mature engineering techniques that ensure these are built in a robust and future-proof manner. …

… In this section, let's explore some real-world machine learning applications. We covered …
The idea is to iteratively reduce the dimensions and bring more relevant dimensions forward. …

… to recent breakthroughs in artificial intelligence (AI) and machine learning (ML). However,
machine learning meets software engineering not only with promising potentials but also with …

… Software engineering for machine learning applications (SEMLA) … ideas regarding the
engineering of ML and artificial engineering (AI) [… : The road ahead,’’ IEEE Softw., vol. 35, no. 5, pp. …