
Regulations
Regulations refer to the set of rules and guidelines that govern the collection, storage, processing, and sharing of data in a particular industry or jurisdiction. In the context of data science and artificial intelligence, regulations are put in place to ensure that data is collected and used in an ethical and responsible manner. These regulations may include requirements for data privacy, security, transparency, and accountability. Compliance with these regulations is essential for organizations that collect and use data, as failure to comply can result in legal and financial consequences. Regulations are constantly evolving as new technologies and use cases emerge, and it is important for organizations to stay up-to-date with the latest regulations in their industry or jurisdiction.
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- Accuracy: Accuracy is a statistical measure that determines how well a machine learning model can predict the outcome of new data. It is the ratio of the number of correct predictions to the total number of predictions made. In other words, accuracy ... Read More >>
- Redundancy: In Data Science, redundancy refers to the duplication of data or information in a dataset or system. Redundancy can occur intentionally or unintentionally, and can have both positive and negative effects on data analysis. On one hand, redun ... Read More >>
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