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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 some effective techniques for handling missing values in large datasets?
RELATED INTERVIEW QUESTIONS
Explain the importance of hyperparameter tuning in improving machine learning models.
What is the concept of feature extraction in computer vision?
What are the common types of clustering algorithms, and how do you choose between them?
What is tuning in machine learning, and how do you apply it to hyperparameters?
What is Principal Component Analysis (PCA) used for in data reduction?
What is the F1-score in classification tasks, and why is it important?
Can you explain the no free lunch theorem in machine learning and its implications on choosing algorithms for different types of problems?
How do you measure the generalization error of a machine learning model?
Explain how you would deal with missing data in a large dataset.
What is causal inference, and how does it differ from correlation analysis?
How would you apply ensemble learning techniques for improving the accuracy of machine learning models?
How do you handle multicollinearity in a dataset, and why is it important to address it before building a model?
How do you apply data smoothing techniques for time-series forecasting?
How do you apply gradient descent in training deep neural networks?
Explain the concept of ensemble learning and its applications in classification and regression problems.
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