Can you complete a take home programming project that involves web scraping data, ETL it, and perform detailed data analysis on it?
Machine Learning Internship Interview Questions
8,210 machine learning internship interview questions shared by candidates
Core discussion on the projects I have done what was the approach how we evaluated the results.
How much familiar are you with open-sourcing?
Q: Tell me about your past projects.
how to describe machine learning to your boss
Kaggle submission for a public competition. Technical questions were about my existing experience and projects I worked in.
How Decision Tree works? Explain how CNN works etc and on Image processing.
Aucune question technique donc pas de piège.
Esperienze passate in Machine Learning? Perché un percorso di ricerca in università?
Floy is a medical AI company on the mission to maximize human healthspan. Our first AI product helps radiologists to improve the diagnostic accuracy for lumbar spine examinations. Diagnostic errors are frighteningly common and statistically affect everyone of us in our lifetime. Radiologists have a 26.1% error rate of clinically relevant findings and 38% of these errors can be prevented through the collaboration of radiologists and AI. It is unacceptable that existing technology is not adopted in radiology. It is time to change that! Our goal is to find out how you approach problems, structure ML projects and obtain tangible results under time constraint. Code quality isless important in this exploratory challenge (production code is a different story). Build a minimal working pipeline with the framework (Tensorflow, PyTorch, etc) of your choice. 1) Structure your ML pipeline. Use different cells with comments to explain you approach. 2) Develop a working pipeline. It does not have to be perfect. Focus on getting things done. 3) Answer three qualitative questions in simple words.
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