Data Scientist 2 Interview Questions and Answers

Use target encoding or frequency encoding to encode categorical columns without increasing feature count.

• Use target encoding: Encode categorical column with the mean of the target variable for each category.

• Use frequency encoding: Encode categorical column with the frequency of each category in the dataset.

• Both methods preserve the information of the categorical column without increasing feature count.

Decision Trees are single trees while Random Forest is a collection of trees. Random Forest grows multiple trees to improve accuracy and reduce overfitting.

• Decision Trees are individual trees that make decisions based on features of the data.

• Random Forest is an ensemble method that combines multiple Decision Trees to improve accuracy and reduce overfitting.

• Random Forest grows a lot of Decision Trees to increase diversity in predictions and reduce the risk of overfitting.

• Each ...read more

Answering common questions related to data science concepts and techniques.

• To handle model overfitting, one can use techniques like cross-validation, regularization, and early stopping. For model underfitting, consider using more complex models or adding more features.

• Standardizing data is important for algorithms like K-Nearest Neighbors and Support Vector Machines. It is not required for tree-based models like Decision Trees and Random Forests.

• Decision Trees work by recursi...read more

Answers to questions related to Linear Regression, K-Means, and SVM in data science.

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

• Euclidean distance formula in K-Means is the square root of the sum of squared differences between two points.

• SVM works by finding the hyperplane that best separates the classes in the feature space.

• SVM on non-linearly separable data uses techniques like kernel trick to map data into hig...read more

Random Forest is like asking a group of friends for advice and making a decision based on majority vote.

• Random Forest is an ensemble learning method that builds multiple decision trees and combines their predictions.

• Each decision tree in the Random Forest is like a friend giving their opinion on a decision.

• The final prediction of the Random Forest is based on the majority vote of all the decision trees.

• For example, if you ask your friends whether you should wear a jacket or n...read more

Covariance measures the extent to which two variables change together, while correlation measures the strength and direction of a linear relationship between two variables.

• Covariance can be positive, negative, or zero, indicating the direction of the relationship between variables.

• Correlation is always between -1 and 1, with 1 indicating a perfect positive linear relationship, -1 indicating a perfect negative linear relationship, and 0 indicating no linear relationship.

• Covari...read more

The research paper explores the impact of artificial intelligence on healthcare outcomes.

• The paper discusses how AI can improve diagnostic accuracy and treatment planning in healthcare.

• It examines the challenges and ethical considerations of implementing AI in medical settings.

• The research paper also highlights the potential benefits of AI in personalized medicine and patient care.

• One example is a study that used AI algorithms to analyze medical imaging data and predict patie...read more

Designing a machine learning system involves selecting appropriate algorithms, data preprocessing, model evaluation, and deployment strategies.

• Understand the problem and define objectives

• Select appropriate algorithms based on the problem (e.g. regression, classification, clustering)

• Preprocess data (e.g. cleaning, normalization, feature engineering)

• Split data into training and testing sets for model evaluation

• Tune hyperparameters to optimize model performance

• Deploy the model i...read more