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HTML
CSS
Python
PHP
MySQL
Linux
Shobha
The best way to predict the future is to invent it
What is Principal Component Analysis (PCA) used for in data reduction?
RELATED INTERVIEW QUESTIONS
What is Collaborative Filtering, and how is it used in building recommendation systems?
What is the difference between deterministic and stochastic models in analytics?
Explain bootstrapping and how it helps with estimating uncertainty in your analysis.
What are the challenges of working with unstructured data, and how can they be overcome?
What is dimensionality reduction, and how does PCA (Principal Component Analysis) help?
What are the different types of machine learning models used for predictive analytics?
What is data lineage, and how does it help in tracking data flow?
Explain how latent variable models work in data analytics.
How do you handle high-dimensional data and reduce the risk of overfitting?
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What are the types of biases in data analysis and how can they be minimized?
What is ensemble learning, and why is it useful in machine learning?
Explain how principal component analysis (PCA) works for dimensionality reduction.
What are the differences between deep learning and ensemble methods in predictive analytics?
What is the role of Bayesian methods in data analytics, and how do they compare to frequentist approaches?
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