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HTML
CSS
Python
PHP
MySQL
Linux
Shobha
The best way to predict the future is to invent it
What is Boosting in machine learning, and how does it work?
RELATED INTERVIEW QUESTIONS
Explain how data integrity is maintained in a multi-source data environment.
What is the difference between bagging and boosting, and how do they impact model performance and accuracy?
What is Gaussian Naive Bayes, and when would you use it in classification?
How do you implement real-time analytics for tracking customer interactions on an e-commerce site?
What is the difference between precision and accuracy in the context of classification problems?
What is tuning in machine learning, and how do you apply it to hyperparameters?
What is the importance of using dropout in deep learning models?
What is a data mart, and how does it differ from a data warehouse in terms of analytical purposes?
How do you ensure that a machine learning model is interpretable for non-technical stakeholders?
How do you calculate the precision, recall, and F1-score for a binary classification model?
How do you perform unsupervised learning for customer segmentation?
What are the common pitfalls in implementing predictive analytics models, and how can they be avoided?
What is the role of visualization in data analysis, and which Python libraries would you use?
What are the differences between bagging and boosting in ensemble methods?
How do you evaluate model performance when the dataset is small and unbalanced?
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