The Johnson Group Head/VP/GM-Administration & Facilities Interview Questions and Answers

Gradient Boost is a machine learning technique that builds models in a sequential manner, where each new model corrects errors made by the previous one.

• Gradient Boost combines multiple weak learners to create a strong learner.

• It focuses on reducing the errors made by the previous models by giving more weight to the misclassified data points.

• Popular implementations include XGBoost, LightGBM, and CatBoost.

• Gradient Boost ...read more

Evaluation metric selection is crucial for assessing the performance of a machine learning model.

• Consider the specific problem domain and objectives of the model

• Choose metrics that align with the business goals

• Select metrics that are easy to interpret and communicate

• Balance between different metrics to get a comprehensive view of model performance

• Examples of evaluation metrics include accuracy, precision, recall, F1 sc

eVar is a conversion variable that captures values at the time of conversion, while prop is a traffic variable that captures values at the time of page view.

• eVar captures values at the time of conversion, while prop captures values at the time of page view.

• eVar is used to track conversion events, while prop is used to track traffic events.

• eVar is persistent across visits, while prop is not.

• Example: eVar can capture the...read more

Clustering is grouping similar data points together while classification is assigning labels to data points based on their features.

• Clustering is unsupervised learning while classification is supervised learning.

• Clustering algorithms include K-means, hierarchical clustering, and DBSCAN.

• Classification algorithms include decision trees, logistic regression, and support vector machines.

• Clustering is used for customer segm...read more