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| From Software Development Lifecycle to Machine Learning Lifecycle
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Marine Alraqdi, Shahad Alqureisha, Reham Alzowaid, Munerah Altalasi, Maram Alsuhaibani, Aisha Al-Maalwy and Omer Alrwais
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Abstract:
Development life cycles are important for developing any system since they include the methodologies and models needed to confirm users understand the design, meet their needs, and ensure the project is on track. Software Development Life Cycle (SDLC) is one of the traditional methods of development software. It lists all the process and task necessary for developing software. But with the rapid development of machine learning that becoming vital in several industries, new methods for life cycle development needed to meet demand, such as Machine learning Life Cycle (MLLC). The main reason for needing (MLLC) due to many differences between machine learning applications and traditional information software. This paper deal with description on how SDLC differs from MLLC at different stages of the development life cycle. In this paper, we first provide brief discussion about SDLC, followed by the definition and importance of MLLC. Finally, we provide a comparison between SDLC and MLLC at different stages of the development life cycle.
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