Improving code vs improving data quality

Andrew Ng: “Traditional software is powered by code, whereas AI systems are built using both code (models + algorithms) and data. When a system isn’t performing well, many teams instinctually try to improve the code. But for many practical applications, it’s more effective instead to focus on improving the data… It is commonly assumed that 80 percent of machine learning is data cleaning. If 80 percent of our work is data preparation, then why are we not ensuring data quality is of the utmost importance for a machine learning team?” Link

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