LG Electronics Research Scientist Interview Questions and Answers

Q1. Exptected salary
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Q2. What do you expect for work
Ans. 
I expect challenging projects, opportunities for growth, collaborative team environment, and work-life balance.
• Challenging projects that allow me to apply my data science skills and learn new techniques

• Opportunities for growth and advancement within the company

• Collaborative team environment where I can share ideas and work together towards common goals

• Work-life balance to ensure I can perform at my best both profession
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Topic was joining and calculating

Q1. Explain xgboost
Ans. 
XGBoost is a popular machine learning algorithm known for its speed and performance in gradient boosting.
• XGBoost stands for eXtreme Gradient Boosting.

• It is an implementation of gradient boosted decision trees designed for speed and performance.

• XGBoost is widely used in machine learning competitions and has become a popular choice for data scientists.

• It can handle missing data and is optimized for parallel processing.

• XG...read more
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Q2. Explain decision tree
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Decision tree is a predictive modeling tool that uses a tree-like graph of decisions and their possible consequences.
• Decision tree is a supervised learning algorithm used for classification and regression tasks.

• It breaks down a dataset into smaller subsets based on different attributes.

• Each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome...read more
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Q1. Data science basics fundamental questions
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Q1. Data science project based
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Q1. Behavioural project based and technical
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Q1. Motivation, behavioral and informative
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Q1. Questions related to Python , ML, Deep Learning and resume based questions
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Q1. Project related
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Q1. Usual HR questions
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I was asked to solve various problems (your typical algorithm and data structure subjects), as well as explain the various projects I worked on in my most recent position.

Divide candidates in a group of around 15 people, and put you through different activities such as role play exercises to measure your communication and team working skills.

Q1. Interview questions were mostly based on basic SQL and python queries
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Q1. Question were asked on machine learning algorithms. There were few questions related to deep learning and image processing.Interviewer has asked me write live code on some moderate level DSA question.
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We had to solve two usecases; forecasting and topic modelling.

Q1. Different clustering methods
Ans. 
Different clustering methods include K-means, hierarchical clustering, DBSCAN, and Gaussian mixture models.
• K-means: partitions data into K clusters based on centroids

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

• DBSCAN: density-based clustering method that groups together points in high-density areas

• Gaussian mixture models: assumes data points are generated from a mixture of Gaussian distribution
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Q1. Why would you join Signify?
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