What are some examples of machine learning in data cleaning?

What are some examples of machine learning in data cleaning?

Machine learning can be used in data cleaning for tasks like anomaly detection, missing value imputation, and data deduplication.

Can you explain how anomaly detection works in this context?

Anomaly detection identifies outliers in data that may indicate errors or unusual patterns, helping to clean the dataset.

What about missing value imputation? How does that work?

Missing value imputation uses algorithms to predict and fill in missing data points based on existing data patterns.

Are there specific algorithms commonly used for these tasks?

Yes, algorithms like k-Nearest Neighbors, Random Forest, and regression models are often used for these data cleaning tasks.