Sony Data Science Intern Interview Questions and Answers

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
Ans. 
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. 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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Q1. 1. diff between acf pacf
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ACF measures the linear relationship between an observation and its lagged values. PACF measures the direct relationship.
• ACF (Autocorrelation Function) measures the correlation between an observation and its lagged values.

• PACF (Partial Autocorrelation Function) measures the correlation between an observation and its lagged values, while removing the indirect effects of intermediate lags.

• ACF is used to identify the orde...read more
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