Why is data cleaning crucial in AI?
An example of an AI chatbot conversation about the importance of data cleaning in AI.
Why is data cleaning crucial in AI?
Data cleaning is essential in AI because it ensures the quality and accuracy of the data used for training models.
What happens if we skip data cleaning?
Skipping data cleaning can lead to biased models, inaccurate predictions, and ultimately, poor decision-making.
Can you give examples of data cleaning techniques?
Sure! Common techniques include removing duplicates, handling missing values, and normalizing data formats.
How often should data cleaning be performed?
Data cleaning should be an ongoing process, ideally performed regularly as new data is collected.
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