Data Science Software Engineer Interview Questions and Answers

Logistic regression is a classification algorithm used to predict binary outcomes.

• Logistic regression uses a sigmoid function to map input values to a probability score.

• The cost function for logistic regression is the negative log-likelihood function.

• Unlike linear regression, logistic regression is used for classification tasks.

• Logistic regression assumes a linear relationship between the input variables and the log-odds of the output variable.

• A disadvantage of logistic regre...read more

Decision trees, bagging, and boosting are techniques used in machine learning to improve model accuracy.

• Decision trees are a type of model that uses a tree-like structure to make predictions.

• Bagging is a technique that involves training multiple models on different subsets of the data and combining their predictions.

• Boosting is a technique that involves iteratively training models on the data, with each subsequent model focusing on the errors of the previous model.

• Both baggin...read more

Dealing with unbalanced data sets requires careful consideration of statistical techniques.

• Use resampling techniques such as oversampling or undersampling to balance the data

• Consider using different evaluation metrics such as precision, recall, and F1 score

• Use ensemble methods such as bagging or boosting to improve model performance

• Consider using anomaly detection techniques to identify rare events in the minority class

• Stratified sampling can be used to ensure that the traini...read more