Wolters Kluwer Data Scientist Interview Questions and Answers

Basic self evaluation test.

Q1. What project I have completed and follow-up questions on that?
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Q2. How to handle class imbalance.
Ans. 
Handling class imbalance involves techniques like resampling, using different algorithms, and adjusting class weights.
• Use resampling techniques like oversampling or undersampling to balance the classes.

• Utilize algorithms that are robust to class imbalance, such as Random Forest, XGBoost, or SVM.

• Adjust class weights in the model to give more importance to minority class.

• Use evaluation metrics like F1 score, precision, r...read more
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Q3. Basic Python coding questions.
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Q1. Data-related questions.
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Q2. ML Ops questions.
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Q1. Basic DS question like how to handle missing features
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Q1. Case study based questions
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Q1. How can Logistic regression be applied for multiclasstext classification
Ans. 
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. How does fbpropher forecasting model works and how is can be used to forecsst trafffic
Ans. 
fbprophet is a forecasting model developed by Facebook that uses time series data to make predictions.
• fbprophet is an open-source forecasting tool developed by Facebook's Core Data Science team.

• It is based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.

• fbprophet can be used to forecast traffic by providing historical data on traffic patterns and usi...read more
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