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HTML
CSS
Python
PHP
MySQL
Linux
Javascript
Shobha
The best way to predict the future is to invent it
Explain how principal component analysis (PCA) works for dimensionality reduction.
RELATED INTERVIEW QUESTIONS
How do you perform feature scaling, and what are its benefits in machine learning?
What are the common pitfalls in implementing predictive analytics models, and how can they be avoided?
How does the k-means clustering algorithm work and when should it be used?
What is hyperparameter tuning, and why is it essential for model optimization? How do you perform hyperparameter tuning effectively?
Explain the difference between supervised and unsupervised learning with examples.
What are active learning methods, and when would you apply them in data analytics?
How do you apply data augmentation in deep learning for image processing?
What are the primary steps involved in preparing data for a machine learning model?
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What is linear programming, and how does it relate to data optimization problems?
What are the benefits of using cloud analytics over on-premise solutions?
How do you use clustering for market segmentation in customer analytics?
How do you choose the appropriate machine learning algorithm for a given dataset or problem? What factors influence your decision?
Can you explain the no free lunch theorem in machine learning and its implications on choosing algorithms for different types of problems?
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