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HTML
CSS
Python
PHP
MySQL
Linux
Javascript
Shobha
The best way to predict the future is to invent it
Explain the concept of regularization in machine learning. How does L1 and L2 regularization differ, and when would you use each?
RELATED INTERVIEW QUESTIONS
Explain the concept of a data pipeline and its components in an analytics workflow.
How do you handle high-dimensional data and reduce the risk of overfitting?
How would you evaluate model performance in an imbalanced dataset problem?
Explain the role of backpropagation in training neural networks.
What is the K-nearest neighbors algorithm, and when would you use it?
How do you decide whether to use a parametric or non-parametric statistical method?
What is Principal Component Analysis (PCA) used for in data reduction?
How would you apply ensemble learning techniques for improving the accuracy of machine learning models?
What is the role of Bayesian methods in data analytics, and how do they compare to frequentist approaches?
How do you apply data augmentation in deep learning for image processing?
How do you optimize the performance of an algorithm when the dataset size is enormous?
How do you assess the impact of outliers in your data and model predictions?
What is regression analysis, and how do you apply it in business analytics?
What are the differences between deep learning and ensemble methods in predictive analytics?
What is the bootstrap method, and how is it used for confidence interval estimation?
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