IntellectFaces Technology Solutions Data Scientist Interview Questions and Answers

Q1. Model evaluation and performance metrices
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Q2. Explaination of bagging and boosting techniques
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Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.
• Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.

• Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.

• Bagging reduces va...read more
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Q1. Question on NER models
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Q2. Question from project
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Q1. Critical thinking questions
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Q2. Case studies based questions
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NER training using deep learning

Q1. Describe the approach taken for assignment
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I approach assignments by breaking them down into smaller tasks, setting deadlines, and regularly checking progress.
• Break down the assignment into smaller tasks to make it more manageable

• Set deadlines for each task to stay on track

• Regularly check progress to ensure everything is on schedule

• Seek feedback from colleagues or supervisors to improve the quality of work
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Q2. Scenario based questions
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Puzzlee on three bulb, switched off, tell which one

Q1. Puzzle - rope burn and length
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Q2. Strength and weakness
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