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HTML
CSS
Python
PHP
MySQL
Linux
Shobha
The best way to predict the future is to invent it
What are the best practices to ensure model interpretability and explainability?
RELATED INTERVIEW QUESTIONS
What is data normalization, and why is it important in machine learning?
What are the common pitfalls when working with real-time data in analytics?
How do you interpret the results of a confusion matrix, and what does it tell you about the performance of a classification model?
Explain the concept of regularization in machine learning. How does L1 and L2 regularization differ, and when would you use each?
What are LSTM networks, and how do they handle sequential data?
What is gradient descent, and how does it work in the training of machine learning models? How do you decide the learning rate?
How do you handle imbalanced datasets in classification problems, and what techniques do you use to improve the model’s performance?
Explain the concept of feature importance in models like Random Forest or Gradient Boosting. How do you assess and interpret feature impor
What are autoencoders, and how are they used in unsupervised learning tasks?
How do you handle high-cardinality categorical features in machine learning models?
What is dimensionality reduction, and why is it important in data analytics?
What is the role of Markov chains in predictive analytics for customer behavior?
How do you deal with skewed data in regression models?
How do you choose the appropriate machine learning algorithm for a given dataset or problem? What factors influence your decision?
What are the common pitfalls in implementing predictive analytics models, and how can they be avoided?
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