Xoriant Data Scientist Interview Questions and Answers

Aptitude, coding on python NLP

Python Data Frames, String list manipulation

Q1. Common discussion
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Q2. Salary location etc
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Q1. Python programming, basic linear regression and logistic regression
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Q1. Linked list, dynamic programming questions
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Code in Python for checking palindromes and SQL for sales data based on months.

Q1. Types of prompting
Ans. 
Prompting is a technique used to encourage a person to continue speaking or to provide more information.
• Verbal prompts: asking open-ended questions, using encouraging words

• Non-verbal prompts: nodding, maintaining eye contact

• Visual prompts: showing images or videos to stimulate conversation
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Q2. Memory handling in conversational
Ans. 
Memory handling in conversational AI involves managing data storage and retrieval efficiently.
• Use efficient data structures to store and retrieve information

• Implement caching mechanisms to reduce memory usage

• Optimize algorithms for processing large amounts of data

• Consider using cloud-based storage solutions for scalability

• Monitor memory usage and performance regularly
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Q1. Complete interview was on project discussion
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Q2. On ensemble models some questions on stats
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Q1. Concepts and tools
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Coding on the tools we use

Q1. Not cleared the round
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The first was a mcq based coding round for campus placement

This was a pairing coding round

Q1. Explain different unsupervised algo
Ans. 
Unsupervised algorithms are used to find patterns in data without labeled outcomes.
• K-means clustering: partitions data into K clusters based on similarity

• Hierarchical clustering: creates a tree of clusters based on similarity

• Principal Component Analysis (PCA): reduces dimensionality by finding orthogonal components

• Association rule mining: discovers interesting relationships between variables in large datasets
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