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HTML
CSS
Python
PHP
MySQL
Linux
Javascript
Shobha
The best way to predict the future is to invent it
Explain how principal component analysis (PCA) works for dimensionality reduction.
RELATED INTERVIEW QUESTIONS
Explain the concept of ensemble learning and its applications in classification and regression problems.
How would you handle an imbalanced dataset in a classification problem?
What is the ROC-AUC curve, and how do you interpret it?
How would you handle noisy data when training a machine learning model?
What is the role of feature scaling in improving machine learning model accuracy?
What is the role of cloud computing in enabling data analytics at scale?
What are the ethical considerations when analyzing customer data in analytics?
How do you ensure that your machine learning model generalizes well on unseen data?
Explain the Naive Bayes algorithm and its application in data analytics.
How do you perform dimensionality reduction, and why is it essential in machine learning?
Explain how an ensemble learning method like Random Forest improves model performance.
How do you perform feature engineering in time-series data?
How do you deal with class imbalance in classification models?
What is data streaming, and how is it used for real-time analytics?
What is time-series forecasting, and how do you handle seasonality in models?
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