Machine Learning
Machine Learning.
Infrastructure
Pre Processing
Cleaning up datasets is of fundamental importance and takes time and requires focused attention.
Context
Links
Questions
Which machine learning principle — generalization versus memorization, model capacity versus data quality, or supervised versus self-supervised learning — most commonly determines whether a model is useful in production?
- At what training data size does the quality of data labeling become more important than adding more data volume?
- How does the shift from task-specific models to foundation models change the machine learning investment calculus for a startup?
- Which ML deployment failure mode — distribution shift, latency, or cost — is most commonly overlooked during development and most costly in production?