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IntroductionMachine learning is about extracting knowledge from data. It is a research field at the intersection of statistics, artificial intelligence, and computer science and is also known as predictive
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Data science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Machine learning, a subset of data science, involves the use of algorithms and statistical models that enable computers to perform tasks without explicit instructions by using patterns and inference instead.
Typically, individuals or organizations involved in data analysis, data management, or machine learning projects may need to file certain reports or documentation regarding their practices, depending on regulatory requirements or internal governance policies.
Filling out data science vs machine reports involves detailing the methodology used in data collection, processing, and analysis, as well as specifying the machine learning algorithms implemented, and documenting results and findings in a clear and transparent manner.
The purpose of data science is to uncover insights and facilitate data-driven decision making through analysis of large datasets. Machine learning aims to develop systems that improve automatically through experience to make predictions or decisions based on data.
Reported information typically includes the methodologies used, parameters of the study, datasets, analytics results, machine learning models applied, validation processes, and any conclusions drawn.
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