Evaluation of machine learning algorithms' performance in digital transformations: a comparative analysis

Abstract

In the realm of digital transformations, the role of machine learning algorithms stands as a critical catalyst for innovation and progress. The integration of machine learning algorithms has become integral in driving digital transformations across various industries. This research paper embarks on a comparative analysis, meticulously evaluating the performance of various machine learning algorithms in the context of driving and shaping digital transformations. Leveraging diverse datasets and real-world case studies, this study delves into the efficacy, adaptability, and limitations of prominent machine learning techniques. Through methodical experimentation and rigorous assessment, this research endeavors to offer valuable insights into the selection and optimization of these algorithms. By shedding light on their strengths and weaknesses, this analysis aims to empower organizations and decision-makers, enabling them to make informed choices when integrating machine learning into their digital transformation strategies. Ultimately, this study seeks to provide a comprehensive understanding of the landscape, assisting in maximizing the potential and impact of machine learning in advancing digital transformations across various industries.