Expleo Solutions Data Science Engineer Interview Questions, Process, and Tips

Handling imbalanced data involves techniques like resampling, using different algorithms, and adjusting class weights.

• Use resampling techniques like oversampling or undersampling to balance the data

• Utilize algorithms that are robust to imbalanced data, such as Random Forest or XGBoost

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

Python code to calculate correlation between two features

• Import pandas library

• Use df.corr() method to calculate correlation between two features

• Specify the two features as arguments to the corr() method

Outliers can be handled by removing, transforming, or imputing them based on the context of the data.

• Identify outliers using statistical methods like Z-score, IQR, or visualization techniques.

• Remove outliers if they are due to data entry errors or measurement errors.

• Transform skewed data using log transformation or winsorization to reduce the impact of outliers.

• Impute outliers with the median or mean if they are valid ...read more

I would communicate openly with the client, provide updates on the progress, and discuss potential solutions to meet the deadline.

• Communicate proactively with the client about the delay

• Provide regular updates on the progress of the task

• Discuss potential solutions to meet the deadline, such as reallocating resources or extending the timeline

• Apologize for the delay and take responsibility for the situation

• Ensure that the...read more