Bosch Global Software Technologies Data Scientist Interview Questions and Answers

Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.

• Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.

• Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.

• Bagging reduces va...read more

Fundamentals of classical machine learning

• Classical machine learning involves algorithms that learn from data and make predictions or decisions.

• Common algorithms include linear regression, decision trees, support vector machines, and k-nearest neighbors.

• Key concepts include training data, testing data, model evaluation, and hyperparameter tuning.

• Classical ML is often used for tasks like classification, regression, clus

There are various ML algorithms such as linear regression, decision trees, random forests, SVM, KNN, neural networks, etc.

• Linear regression is used for predicting continuous values

• Decision trees and random forests are used for classification and regression

• SVM is used for classification and regression

• KNN is used for classification and regression

• Neural networks are used for complex problems such as image recognition and