Data
Data refers to any collection of information that is stored, processed, and analyzed to derive insights and knowledge. In the context of data science, data can be structured or unstructured, and can come from a variety of sources such as databases, sensors, social media, and more. Data is the foundation of all data-driven decision making and machine learning algorithms, and is used to train models, make predictions, and identify patterns and trends. Data can be preprocessed and cleaned to remove noise and inconsistencies, and can be transformed and visualized to gain a better understanding of the underlying patterns and relationships. Data is often categorized into different types such as numerical, categorical, and text, and can be analyzed using a variety of statistical and machine learning techniques.
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- Data Quality Issues: Data Quality Issues refer to problems or inconsistencies in data that affect its accuracy, completeness, consistency, and reliability. These issues can arise from various sources such as human error, system errors, data entry errors, data i ... Read More >>
- Frameworks: In Data Science and Artificial Intelligence, a framework is a set of pre-written code that provides a standard way of building and deploying applications. It is a collection of libraries, modules, and tools that developers use to create com ... Read More >>
- Weight: In data science, weight refers to the importance or significance of a feature or variable in a machine learning model. Weights are assigned to each feature or variable based on their impact on the output of the model. The higher the weight, ... Read More >>
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