What are the common data processing methods used in machine learning?
An example of an AI chatbot conversation about data processing methods in machine learning.
What are the common data processing methods used in machine learning?
Common data processing methods include normalization, standardization, encoding categorical variables, and handling missing values.
Can you explain normalization and why it's important?
Normalization scales the data to a range of [0, 1], which helps improve the performance of algorithms sensitive to the scale of data.
What about standardization? How does it differ from normalization?
Standardization transforms data to have a mean of 0 and a standard deviation of 1, making it useful for algorithms that assume normally distributed data.
How do I handle missing values in my dataset?
You can handle missing values by removing them, imputing with mean/median/mode, or using algorithms that support missing data.
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