How to Stand Out in Machine Learning Interviews: A Framework for ML System Design | HackerNoon
Briefly

from Hackernoon2 years ago
The task in an MLE interview is usually presented from a business perspective; thus, it's crucial to clarify requirements before proposing solutions.
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Data is critical for model success. Identifying available data sources and understanding their structure can significantly influence model performance and outcomes.
Hackernoonhttps://hackernoon.com/how-to-stand-out-in-machine-learning-interviews-a-framework-for-ml-system-design
Model training should only occur after careful task clarification and data understanding to ensure accurate and applicable solutions.
Hackernoonhttps://hackernoon.com/how-to-stand-out-in-machine-learning-interviews-a-framework-for-ml-system-design
When it comes to model inference, it's important to consider how inference will be executed after the model is trained, to ensure practical application.
Hackernoonhttps://hackernoon.com/how-to-stand-out-in-machine-learning-interviews-a-framework-for-ml-system-design
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#mle-interviews #machine-learning #data-management #model-training #ml-system-design
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