How does data quality impact machine learning models?

How does data quality impact machine learning models?

Data quality is crucial for machine learning as it directly affects model accuracy and performance. Poor quality data can lead to biased or incorrect predictions.

What are some common data quality issues?

Common data quality issues include missing values, duplicates, inconsistencies, and outliers. Addressing these is essential for effective modeling.

How can I improve data quality for my project?

You can improve data quality by implementing data validation checks, cleaning the data, and using robust data collection methods.

Are there tools available for data quality assessment?

Yes, there are several tools like Talend, Trifacta, and Apache Griffin that can help assess and improve data quality.