Deep Learning Interview Questions and Answers
Ques 26. Explain the concept of imbalanced classes in classification problems and potential solutions.
Imbalanced classes occur when one class in a classification problem has significantly fewer instances than the others. Solutions include resampling techniques (oversampling or undersampling), using different evaluation metrics (precision, recall, F1 score), and incorporating class weights during training.
Ques 27. What is the role of the softmax function in a neural network's output layer?
The softmax function is used in the output layer of a neural network for multi-class classification. It converts raw output scores into probability distributions, ensuring that the sum of the probabilities across all classes is equal to one. It helps in making a probabilistic prediction for each class.
Ques 28. Explain the concept of attention mechanisms in neural networks and their applications.
Attention mechanisms allow a model to focus on specific parts of the input sequence when making predictions. They are commonly used in natural language processing tasks, such as machine translation, where the model needs to selectively attend to relevant words or tokens in the input.
Ques 29. What is the difference between a regression problem and a classification problem in machine learning?
In a regression problem, the goal is to predict a continuous output, such as a numerical value. In a classification problem, the goal is to assign inputs to one of several predefined categories. Regression models predict quantities, while classification models assign labels.
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