Which step in the machine learning process transforms data into a structured format by removing missing data and corrupted observations?
- Testing data
- Learning data
- Preparing data
- Model evaluation
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Answers Explanation & Hints: The step in the machine learning process that transforms data into a structured format by removing missing data and corrupted observations is called Data Preparation. Data preparation, also known as data cleaning or data preprocessing, is a critical step in the machine learning process that involves transforming raw data into a format that can be used by the learning algorithm. This includes identifying and handling missing or corrupted data, handling outliers and anomalies, transforming data types, and normalizing or scaling data to a common range. Data preparation is essential to ensure the quality and accuracy of the machine learning model, as the quality of the input data can significantly impact the accuracy of the model’s predictions. |