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While ML algorithm design may not be the primary role of ML solutions architects, it is still essential for them to possess a comprehensive understanding of common real-world ML algorithms and their applications in solving business problems. This knowledge empowers ML solutions architects to identify suitable data science solutions and design the necessary technology infrastructure for deploying these algorithms effectively.By familiarizing themselves with a range of ML algorithms, ML solutions architects can grasp the strengths, limitations, and specific use cases of each algorithm. This enables them to evaluate business requirements accurately and select the most appropriate algorithmic approach to address a given problem. Whether it's classification, regression, clustering, or recommendation systems, understanding the underlying algorithms equips architects with the knowledge required to make informed decisions...