What is data quality in machine learning?

What is data quality in machine learning?

Data quality in machine learning refers to the accuracy, completeness, and reliability of the data used for training models.

Why is data quality important for machine learning models?

High data quality ensures that models learn from accurate information, leading to better predictions and performance.

How can I improve data quality for my machine learning project?

You can improve data quality by cleaning the data, removing duplicates, handling missing values, and validating data sources.

What tools can help with data quality assessment?

Tools like Talend, Apache Nifi, and DataRobot can help assess and improve data quality in your projects.