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HTML
CSS
Python
PHP
MySQL
Linux
Javascript
Shobha
The best way to predict the future is to invent it
What are the common pitfalls when working with real-time data in analytics?
RELATED INTERVIEW QUESTIONS
How do you implement real-time analytics for tracking customer interactions on an e-commerce site?
How do you identify and resolve data leakage in machine learning models?
What is time-series analysis, and what techniques do you use for it?
What is causal inference, and how does it differ from correlation analysis?
What is the importance of data cleaning in data analytics, and what techniques would you use?
What is dimensionality reduction, and how does PCA (Principal Component Analysis) help?
What is the role of natural language processing in analyzing customer feedback?
Explain the concept of data wrangling and its importance in data analytics.
What is stratified sampling, and when should it be used in machine learning?
What are the advantages and disadvantages of using deep learning for structured data analysis?
Explain how you would approach feature engineering for a time-series dataset.
Explain the concept of a precision-recall curve and when to use it.
How do you apply nearest neighbor algorithms for recommendation systems?
What is latent variable modeling, and how is it used in dimensionality reduction techniques such as factor analysis or topic modeling?
Explain bootstrapping and how it helps with estimating uncertainty in your analysis.
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