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5. Explain Logistic Regression and it's optimization.

Machine Learning Basics, Deep Learning Basics

Medium

7. What is Cross Entropy Loss?

Machine Learning Basics

Easy

8. What is F1-Score? Define it in terms of Precision and Recall.

9. What is bias variance trade-off? How does it impact model performance?

10. What is Batch Normalization? How it works as regularization?

Advanced Deep Learning

11. Why deep learning models needs epochs for training?

Deep Learning Basics

12. Explain Gradient Descent optimization approach.

14. What is overfitting? How to detect and avoid overfitting?

16. What loss functions can be used for regression? Which one is better for outliers?

25. What is Linear Regression? What are the assumptions of a Linear Regression Model?