Applied Cloud Computing Data Scientist Interview Questions, Process, and Tips

Random forest is an ensemble learning method using decision trees, while XGBoost is a gradient boosting algorithm.

• Random forest builds multiple decision trees and combines their predictions, while XGBoost builds trees sequentially to correct errors.

• Random forest is less prone to overfitting compared to XGBoost.

• XGBoost is computationally efficient and often outperforms random forest in terms of predictive accuracy.

• Rando...read more

I convince clients of model usefulness by showcasing its accuracy, precision, recall, and F1 score.

• Explain the model's accuracy in predicting outcomes compared to actual results

• Discuss precision - the proportion of true positive predictions out of all positive predictions

• Highlight recall - the proportion of true positive predictions out of all actual positives

• Mention F1 score - the balance between precision and recall,

I collect data from clients through various methods such as surveys, interviews, API integrations, and data sharing agreements.

• Conduct surveys to gather specific data points from clients

• Interview clients to understand their data needs and preferences

• Integrate with client's systems through APIs to access real-time data

• Establish data sharing agreements to receive data from clients securely

Tuned hyperparameters include learning rate, batch size, number of layers, and activation functions.

• Adjusted learning rate to improve model convergence

• Optimized batch size for better training efficiency

• Experimented with different numbers of layers to find optimal model complexity

• Tried various activation functions to enhance model performance

The features in the data set include age, gender, income, education level, location, and purchase history.

• Age

• Gender

• Income

• Education level

• Location

• Purchase history