Answer Posted / Manish Rawat

When a file is corrupted or missing from the dataset, it can lead to errors and inconsistencies during training. To handle this situation, several strategies can be employed: (1) Data imputation: filling missing values with statistical estimates like mean, median, or mode; (2) Deleting the row or instance if the missingness is not random; (3) Using external sources to recover the missing data; (4) Replacing corrupted files with good versions.

What are the apis outside tensorflow project?

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