Encora Data Scientist Interview Questions and Answers

Q1. General ML questions
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Q2. General dl. Questions
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Q1. Questions around the previous work
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Q2. Questions around how re-rank work, and image segmentation,
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Q3. Questions with podman and docker
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Q1. Project that I worked on
Ans. 
Developed a predictive model for customer churn in a telecom company
• Used machine learning algorithms like logistic regression and random forest

• Analyzed customer data such as call duration, plan details, and customer complaints

• Achieved 85% accuracy in predicting customer churn
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Q2. Use case only verbal communication
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Code in Python for checking palindromes and SQL for sales data based on months.

Q1. Data science related areas
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Case study related to semantic search

Q1. Questions based on case study
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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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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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