Data Processing Techniques
Data processing techniques refer to the methods and tools used to transform raw data into meaningful and useful information. These techniques involve a series of steps, including data collection, cleaning, integration, transformation, analysis, and visualization. Data processing techniques are essential in data science and artificial intelligence as they enable the extraction of insights and knowledge from large and complex datasets. The choice of data processing techniques depends on the type and quality of data, the research question, and the available resources. Some common data processing techniques include data mining, machine learning, natural language processing, statistical analysis, and data visualization.
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