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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 gradient descent and its variants, and how are they used in machine learning?
RELATED INTERVIEW QUESTIONS
Explain the concept of data wrangling and its importance in data analytics.
What is the role of unsupervised learning in anomaly detection?
How does ensemble learning work, and when should it be applied?
What is data leakage, and how can you prevent it in your analytics projects?
How do you handle a large dataset that does not fit into memory?
How do you handle high-cardinality categorical features in machine learning models?
What are the differences between deep learning and ensemble methods in predictive analytics?
How would you measure the impact of an analytics model in a business setting?
What is XGBoost, and how does it differ from other boosting algorithms?
How do you handle multicollinearity in a dataset, and why is it important to address it before building a model?
How do you use time-series decomposition to analyze seasonal trends?
What is data normalization, and why is it important in machine learning?
How do you apply data smoothing techniques for time-series forecasting?
What are the advantages of using convolutional neural networks (CNN) in image analytics?
How do you measure the generalization error of a machine learning model?
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