How does data quality affect machine learning models?

How does data quality affect machine learning models?

Data quality is crucial for machine learning models as it directly influences their accuracy and reliability. Poor quality data can lead to biased results and incorrect predictions.

Can you give me examples of poor data quality?

Sure! Examples include missing values, incorrect labels, duplicate entries, and outliers that don't represent the true data distribution.

What are the consequences of using low-quality data?

Using low-quality data can result in overfitting, underfitting, and ultimately, a model that fails to generalize well to new data.

How can I improve data quality for my models?

You can improve data quality by cleaning the data, validating it, removing duplicates, and ensuring proper data collection methods.