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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 active learning methods, and when would you apply them in data analytics?
RELATED INTERVIEW QUESTIONS
How do you handle high-cardinality categorical features in machine learning models?
What is the significance of hypothesis testing in data analysis?
How does k-fold cross-validation work, and how do you decide on the value of k for a given dataset?
What is the learning rate in deep learning, and how do you optimize it?
What is the accuracy paradox and how does it affect model evaluation?
Can you explain the no free lunch theorem in machine learning and its implications on choosing algorithms for different types of problems?
What is the importance of using dropout in deep learning models?
What is the role of Bayesian methods in data analytics, and how do they compare to frequentist approaches?
How do you handle categorical data in machine learning models?
Explain the concept of a data pipeline and its components in an analytics workflow.
What is the difference between a data pipeline and an ETL pipeline in terms of analytics?
What is the role of data normalization in machine learning?
What are the different types of feature engineering methods and how do they impact model performance?
What are the advantages and disadvantages of using deep learning for structured data analysis?
How does dimensionality reduction improve the performance of machine learning algorithms?
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