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HTML
CSS
Python
PHP
MySQL
Linux
Shobha
The best way to predict the future is to invent it
What are the differences between bagging and boosting in ensemble methods?
RELATED INTERVIEW QUESTIONS
How do you handle imbalanced datasets in classification models?
How do you handle multivariate time series data for forecasting?
What are recurrent neural networks (RNNs), and how do they handle time-series data?
How do you perform dimensionality reduction, and why is it essential in machine learning?
How would you perform data aggregation for summarizing large datasets?
How would you apply cross-validation to avoid overfitting in a machine learning model?
How do you handle missing data in large datasets using imputation techniques?
What is the accuracy paradox and how does it affect model evaluation?
What is the role of Bayesian methods in data analytics, and how do they compare to frequentist approaches?
Explain how an ensemble learning method like Random Forest improves model performance.
How do you evaluate model robustness to different types of input data?
Explain the concept of gradient boosting and its advantages over traditional decision trees.
How do support vector machines (SVM) work, and why are they used in classification problems?
How do you apply data smoothing techniques for time-series forecasting?
Explain the role of feature scaling in improving the performance of machine learning algorithms.
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