How would you design a machine learning pipeline?
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To answer this question, start by briefly explaining what a machine learning pipeline is. Then, describe the various stages involved, such as data collection, data cleaning, feature extraction, model selection, training, testing, and deployment. Mention the tools or software that can be used at each stage and explain how you would monitor and maintain the pipeline to ensure optimal performance. Use real-world examples or scenarios where possible to illustrate your points.
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Hard Difficulty
Hard questions require advanced understanding and critical thinking. Here, your problem-solving skills are key, as these questions often involve complex scenarios needing in-depth analysis and well-structured responses.
Technical question
Technical questions probe into your industry-specific knowledge and skills. They require precise answers and are an opportunity to show your expertise and practical abilities in your field.