AlgoSec Sdet Lead Interview Questions and Answers

Bias-variance tradeoff is the balance between overfitting and underfitting in machine learning models.

• Bias is the error due to assumptions made in the learning algorithm, while variance is the error due to sensitivity to small fluctuations in the training set.

• High bias leads to underfitting, while high variance leads to overfitting.

• The goal is to find the sweet spot between bias and variance that minimizes the overall ...read more

To overcome underfitting and overfitting, one can use techniques like cross-validation, regularization, and increasing data size.

• Use cross-validation to evaluate the model's performance on unseen data

• Regularize the model by adding penalties to the loss function to prevent overfitting

• Increase the size of the training data to reduce underfitting

• Use ensemble methods like bagging and boosting to reduce overfitting

• Reduce th...read more

SPI testing is a type of software testing that focuses on measuring the performance of a system or application.

• SPI testing involves measuring the performance of a system or application against predefined metrics.

• Tools commonly used for SPI testing include JMeter, LoadRunner, and Gatling.

• REST API testing involves testing the functionality and performance of RESTful web services.

• Other skills I have experience in include ...read more