Скачать или смотреть 12 | Handling Imbalance Data | Data Science

Imbalanced data refers to a situation where the number of instances
belonging to one class in a dataset is much higher than the other class(es).
This can cause problems when training machine learning models, as the
model may be biased toward the majority class and perform poorly on the
minority class.

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Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data.
Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.

A data scientist is a professional who creates programming code and combines it with statistical knowledge to create insights from data.