How do I clean my dataset for machine learning?

How do I clean my dataset for machine learning?

Cleaning a dataset involves removing duplicates, handling missing values, and correcting inconsistencies. What specific issues are you facing?

I have a lot of missing values in my dataset. What should I do?

You can either remove rows with missing values, fill them with a statistic like the mean or median, or use algorithms that can handle missing data. Which approach do you prefer?

I think filling them with the mean is a good idea. How do I do that?

You can use libraries like Pandas in Python. For example, you can use df.fillna(df.mean()) to fill missing values with the mean.

Thanks! What about outliers? How should I handle them?

Outliers can be handled by removing them, transforming the data, or using robust statistical methods. It depends on your analysis goals.