InfoQ - .NET - Presentations https://www.infoq.com InfoQ .NET Presentations feed Presentation: Why Most Machine Learning Projects Fail to Reach Production and How to Beat the Odds https://www.infoq.com/presentations/ml-pitfalls/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=.NET-presentations <img src="/load/view.php?a=aHR0cHM6Ly9yZXMuaW5mb3EuY29tL3ByZXNlbnRhdGlvbnMvbWwtcGl0ZmFsbHMvZW4vbWVkaXVtaW1hZ2UvV2VuamllWkktbWVkaXVtLTE3MzcxMjQ5MDk0NjkuanBn"/><p>Wenjie Zi discusses common pitfalls that cause these failures, such as the inherent uncertainty of machine learning, misaligned optimization objectives, and skill gaps among practitioners.</p> <i>By Wenjie Zi</i> QCon San Francisco 2024 Transcripts Best Practices Machine Learning .NET AI, ML & Data Engineering presentation Fri, 24 Jan 2025 09:30:00 GMT https://www.infoq.com/presentations/ml-pitfalls/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=.NET-presentations Wenjie Zi 2025-01-24T09:30:00Z /presentations/ml-pitfalls/en