Angel One Interview Questions, Process, and Tips

The number of records returned by different types of joins can vary based on the relationship between the tables being joined.

• Inner join returns only the records that have matching values in both tables

• Left join returns all records from the left table and the matched records from the right table

• Right join returns all records from the right table and the matched records from the left table

• Full outer join returns all rec...read more

I have been working as a Senior Process Trainer for the past 5 years, leading training sessions and developing training materials.

• Led training sessions for new hires and existing employees on various processes and systems

• Developed training materials such as manuals, presentations, and online modules

• Conducted assessments and evaluations to measure training effectiveness

• Collaborated with stakeholders to identify training...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 Decisi...read more

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.

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 d...read more

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 diversi...read more