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I applied via Naukri.com and was interviewed before Jan 2024. There were 2 interview rounds.
Bias-variance tradeoff is the balance between underfitting and overfitting in machine learning models.
Bias refers to the error introduced by approximating a real-world problem, variance refers to the error introduced by modeling the noise in the training data.
High bias can cause underfitting, where the model is too simple to capture the underlying patterns in the data.
High variance can cause overfitting, where the mode...
PCA is a dimensionality reduction technique that transforms data into a lower-dimensional space. Feature selection is the process of selecting a subset of relevant features for use in model training.
PCA helps in reducing the dimensionality of data by finding the principal components that explain the most variance in the data.
Feature selection involves selecting the most important features from the dataset based on cert...
Delete removes rows one by one, while truncate removes all rows at once.
Delete is a DML command and can be rolled back, while truncate is a DDL command and cannot be rolled back.
Delete triggers delete triggers and fires delete triggers, while truncate does not trigger any triggers.
Delete is slower as it logs individual row deletions, while truncate is faster as it logs the deallocation of the data pages.
Delete can have...
Developed a machine learning model to predict customer churn in a telecom company.
Used historical customer data to train the model
Features included customer demographics, usage patterns, and customer service interactions
Implemented a random forest algorithm for prediction
Achieved an accuracy of 85% on test data
I have deployed models using cloud services like AWS SageMaker and monitored them using tools like Prometheus and Grafana.
Deployed models using AWS SageMaker for easy scalability and management
Utilized Prometheus and Grafana for monitoring model performance and health
Set up alerts for abnormal behavior or performance degradation
Regularly reviewed logs and metrics to ensure model is functioning as expected
Implement algorithm from scratch
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I want to join IBM because of its reputation as a leading technology company and its commitment to innovation.
IBM is known for its cutting-edge technology and solutions.
The company has a strong focus on research and development.
IBM offers excellent career growth opportunities and a supportive work environment.
Working at IBM would allow me to collaborate with talented professionals from diverse backgrounds.
IBM's global ...
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