Google Machine Learning Software Engineer Interview Questions and Answers

Linear Regression is a statistical method to model the relationship between a dependent variable and one or more independent variables.

• Linear Regression is used to predict a continuous output based on one or more input features.

• The cost function for Linear Regression is the Mean Squared Error (MSE), which measures the average squared difference between the predicted values and the actual values.

• The goal of Linear Regre...read more

Assumptions in Linear Regression and Gaussian Noise origins

• Assumptions in Linear Regression include linearity, independence of errors, homoscedasticity, and normality of errors.

• Gaussian Noise assumption comes from the assumption that the errors in the model follow a Gaussian distribution.

• The Gaussian Noise assumption allows for the use of maximum likelihood estimation in linear regression models.

• If the errors do not fo...read more

Handled disagreement by calmly discussing concerns and finding common ground.

• Approached the manager/client in a respectful and professional manner

• Listened to their perspective and concerns without interrupting

• Expressed own thoughts and concerns clearly and calmly

• Worked together to find a compromise or solution that satisfied both parties

Logistic regression is a statistical method used to analyze and model the relationship between a dependent variable and one or more independent variables.

• Logistic regression is used for binary classification problems.

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

• The model is trained using maximum likelihood estimation.

• The cost function used is the negative log-likelihood function.

• Regularization ...read more