Machine Learning Projects Face High Failure Rates, But Experts Offer Strategies for Success

Examination of a recent presentation at QCon SF 2024 reveals that machine learning (ML) projects face significant challenges in reaching production. According to statistics cited by presenter Wenjie Zi, historical studies show failure rates as high as 85%, with little improvement noted in recent research. The presentation highlighted five common pitfalls in ML projects, including tackling the wrong problem, data quality issues, and integration challenges.

Source: https://www.infoq.com/news/2024/11/why-ml-fails/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global