logseq/logseq/.recycle/pages_hls__Studer et al_2021_Towards CRISP-ML(Q).md

file-path:: file://C:\Users\david\Zotero/storage/VY7ZE3X7/Studer et al_2021_Towards CRISP-ML(Q).pdf file:: [Studer et al_2021_Towards CRISP-ML(Q).pdf](file://C:\Users\david\Zotero/storage/VY7ZE3X7/Studer et al_2021_Towards CRISP-ML(Q).pdf) title:: hls__Studer et al_2021_Towards CRISP-ML(Q)

• Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet business expectations ls-type:: annotation hl-page:: 1 id:: 62ffedc9-0c39-477a-99b4-6c3f13a918f7
• he following second section describes the related work and ongoing research in the development of process models for machine learning applications. In the third chapter, the tasks and quality assurance methodology are introduced for each process phase. Finally, a conclusion and an outlook are given in the fourth chapter. ls-type:: annotation hl-page:: 2 id:: 62ffedea-12ac-4afe-b95a-0f505678c959