HDFC Bank Interview Questions and Answers

Bagging and boosting are ensemble learning techniques. XgBoost is a gradient boosting algorithm.

• Bagging involves training multiple models on different subsets of the data and combining their predictions.

• Boosting involves training models sequentially, with each model trying to correct the errors of the previous model.

• XgBoost is an optimized implementation of gradient boosting that uses a combination of tree-based models and regularization techniques.

• XgBoost is commonly used in...read more

Developed a predictive model to identify potential customer churn for a telecom company

• Performed exploratory data analysis to identify key features affecting customer churn

• Preprocessed data by handling missing values and encoding categorical variables

• Built and compared various machine learning models including logistic regression, decision tree, and random forest

• Tuned hyperparameters using grid search and cross-validation

• Achieved an accuracy of 85% and identified key factors ...read more

Developed a machine learning model to predict customer churn for a telecom company.

• Used logistic regression and decision tree algorithms for classification.

• Performed feature engineering to extract relevant features from customer data.

• Achieved an accuracy of 85% on the test set.

• Provided actionable insights to the company to reduce customer churn.

I have experience in deploying and managing applications on AWS cloud platform.

• Deployed and managed a web application on AWS Elastic Beanstalk

• Used AWS Lambda for serverless computing

• Configured and managed EC2 instances for various projects

• Used S3 for storing and retrieving data

• Set up and managed RDS instances for databases

• Used CloudFormation for infrastructure as code

• Implemented auto-scaling and load balancing for high availability

• Used CloudWatch for monitoring and logging

• Imp...read more

Different performance metrics are used to measure the effectiveness of a model or system.

• Accuracy

• Precision

• Recall

• F1 Score

• ROC Curve

• AUC

• Mean Squared Error

• Root Mean Squared Error

• R-squared