Clarivate Data Scientist Interview Questions and Answers

Q1. Explain chi square distribution. What are the assumptions involved?
Ans. 
Chi square distribution is a probability distribution used in statistical tests to determine the significance of relationships between categorical variables.
• Chi square distribution is a continuous probability distribution that is used in statistical tests such as the chi square test.

• It is skewed to the right and its shape is determined by the degrees of freedom.

• Assumptions involved in chi square distribution include: r...read more
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Q2. Explain different clustering algorithms
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Clustering algorithms group similar data points together based on certain criteria.
• K-means: partitions data into K clusters based on centroids

• Hierarchical clustering: creates a tree of clusters

• DBSCAN: density-based clustering algorithm

• Mean Shift: shifts centroids to maximize data points within a certain radius

• Gaussian Mixture Models: assumes data points are generated from a mixture of Gaussian distributions
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Q1. Deep dive into clustering and bagging boosting algorithms
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Clustering and bagging boosting algorithms are popular techniques in machine learning for grouping data points and improving model accuracy.
• Clustering algorithms like K-means, DBSCAN, and hierarchical clustering are used to group similar data points together based on certain criteria.

• Bagging algorithms like Random Forest create multiple subsets of the training data and train individual models on each subset, then combi...read more
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Q1. Different situation based questions
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Q1. What are the projects worked
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Q2. How familiar are you with LLMs
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Q1. Why are you interested in this role
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Q2. Provide an example how you solved a problem
Ans. 
I solved a problem by using machine learning algorithms to predict customer churn for a telecom company.
• Identified relevant data sources such as customer demographics, usage patterns, and customer service interactions.

• Preprocessed and cleaned the data to handle missing values and outliers.

• Built and trained a machine learning model using algorithms like logistic regression and random forest.

• Evaluated the model's perform...read more
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Q1. How can Logistic regression be applied for multiclasstext classification
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Logistic regression can be applied for multiclasstext classification by using one-vs-rest or softmax approach.
• One-vs-rest approach: Train a binary logistic regression model for each class, treating it as the positive class and the rest as the negative class.

• Softmax approach: Use the softmax function to transform the output of the logistic regression into probabilities for each class.

• Evaluate the model using appropriate...read more
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Q1. Tell me a project you did in school that shows innovation?
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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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