Hewlett Packard Enterprise Senior Data Scientist Interview Questions and Answers

Q1. Question From Regression, classification and clustering Algorithm.
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Q2. Bagging and boosting
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Q3. How to handel less dataset for regression problems
Ans. 
Use techniques like regularization, feature selection, cross-validation, and data augmentation.
• Utilize regularization techniques like Lasso or Ridge regression to prevent overfitting.

• Perform feature selection to focus on the most important variables and reduce noise.

• Use cross-validation to assess model performance and generalizability.

• Consider data augmentation techniques like synthetic data generation or bootstrapping...read more
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Q4. Python Coding and some scenario based ML question.
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Q1. Question from My project and mentioned skills in resume
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Q2. How will you lead team and what your ways.
Ans. 
I will lead by setting clear goals, providing guidance, fostering collaboration, and recognizing team achievements.
• Set clear goals and expectations for the team

• Provide guidance and support to team members

• Foster collaboration and communication within the team

• Recognize and reward team achievements

• Lead by example and demonstrate strong work ethic
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Q1. Salary and Notice period
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Q1. Deep questions about Machine learning, Deep learning, Generative AI, the working of transformers etc.
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Q1. Deep questions about Machine learning and deep learning with projects done. This was a client round.
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Q1. Salary discussion, project discussion, why change? Why Wipro
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Q1. Basics of Machine Learning, Gradient Descent, Trade-off, etc.
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It was based on logical reasoning and verbal along with speech recognition

Python based basic questions like sort find maximum

Q1. They asked all the questions based on my projects.
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Q1. Simple he procedure
Ans. 
Simple procedure refers to a straightforward and easy-to-follow set of steps or instructions.
• Follow a clear sequence of steps

• Use simple language and visuals if needed

• Ensure the procedure is easy to understand and execute
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Q1. Explain BERT Model Architecture and It differs form GPT
Ans. 
BERT is a bidirectional transformer model for pre-training language representations, while GPT is a generative model.
• BERT is a pre-training model that learns contextual representations of words by considering both left and right context.

• GPT is a generative model that uses a transformer decoder to generate text based on the context.

• BERT is bidirectional, meaning it can understand the context of a word by looking at both...read more
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Q1. Almost everything from statistics to EDA & ML models
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Q1. Mostly on projects I've already done, especially on last project and project of the interviewer
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Q1. What are your salary expectations?
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Q2. What is your family background?
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Q3. Share details of your previous job.
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Q4. Why should we hire you?
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Q5. Why are you looking for a change?
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Q6. Tell me about yourself.
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Q1. 1. 2 python coding questions. First one was to find common elements between given 2 arrays. Second was to reverse the string and return back. 2. Discussions on project, Machine learning, Deep learning conc...read more
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Q1. 1.Discussions on project, one case study given related to data science and other behavioral questions asked.
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Q1. ML and python questions at depth
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