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HTML
CSS
Python
PHP
MySQL
Linux
Javascript
Shobha
The best way to predict the future is to invent it
What is Gaussian Naive Bayes, and when would you use it in classification?
RELATED INTERVIEW QUESTIONS
What is the accuracy paradox and how does it affect model evaluation?
Explain how an ensemble learning method like Random Forest improves model performance.
What is latent variable modeling, and how is it used in dimensionality reduction techniques such as factor analysis or topic modeling?
Explain the concept of gradient boosting and its advantages over traditional decision trees.
Explain the concept of regularization in machine learning. How does L1 and L2 regularization differ, and when would you use each?
How do you ensure reproducibility in your data analysis pipelines?
How do you balance the trade-off between bias and variance in machine learning?
Explain the importance of hyperparameter tuning in improving machine learning models.
How do you address skewed data distributions in machine learning models?
Explain the role of feature scaling in improving the performance of machine learning algorithms.
Explain the difference between supervised and unsupervised learning with examples.
Explain how hyperparameter optimization improves machine learning model performance.
How does regularization help to reduce overfitting in machine learning models?
What is the concept of a confusion matrix, and how do you interpret its results in classification models?
What are the best practices for analyzing real-time data streams?
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