What are some common mistakes in AI deployment?
An example of an AI chatbot conversation about common mistakes in AI deployment.
What are some common mistakes in AI deployment?
Some common mistakes include lack of clear objectives, insufficient data quality, and ignoring user feedback.
How can I avoid these mistakes?
To avoid these mistakes, ensure you have clear goals, invest in data quality, and establish a feedback loop with users.
What role does data quality play in AI deployment?
Data quality is crucial as it directly impacts the model's performance and the accuracy of predictions.
Can you give examples of poor data quality?
Examples include missing values, outdated information, and biased datasets that can lead to skewed results.
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