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ML Engineers in Action

Shreya shares insights from ML engineers responsible for models in production, emphasizing the importance of retraining models to address prediction complaints. Lukas and Shreya discuss the use of neural networks in unstructured data like image-heavy applications, highlighting the need for traditional data quality practices in this domain.
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    Gradient Dissent - A Machine Learning Podcast

    Operationalizing Machine Learning: Interview with Shreya Shankar

  • Related Questions

    • Is data quality overlooked in machine learning as discussed in the episode Shreya Shankar: Machine Learning in the Real World and the clip Data Quality Challenges?

    • What are practical examples of structured thinking in the context of the episode Fixing Your ML Data Blind Spots // Yash Sheth // MLOps Coffee Sessions #102 and the clip Unifying Model Architectures from the episode \[MINI] Structured and Unstructured Data?

    • Do companies need large machine learning teams, as discussed in the episode MLOps Coffee Sessions #13 How to Choose the Right Machine Learning Tool: A Conversation // Jose Navarro and Mariya Davydova, and the clip ML Infrastructure Standardization?

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