Regularization Methods — past-year questions
Deep Learning (CSC701) · Semester 7 · Module 2 · AIML & Data Science
9 past-year questions on Regularization Methods have appeared in Mumbai University CSC701 papers between 2023–2026, 10 times in total. Every question is shown in full below with its marks and repeat count. Model answers require a free account.
Questions asked on Regularization Methods
- 1.
Explain the dropout method and it's advantages.
5M2× seenlast asked 2024 - 2.
Explain the need for regularization in deep neural networks. Discuss various regularization techniques used to reduce overfitting.
10M1× seenlast asked 2026 - 3.
Identify the problem when a deep learning model achieves high training accuracy but low validation accuracy. Suggest suitable solutions.
10M1× seenlast asked 2026 - 4.
Explain the concept of overfitting and under fitting in neural network.
5M1× seenlast asked 2025 - 5.
Explain regularization in neural network.
5M1× seenlast asked 2025 - 6.
Explain the L1 and L2 regularization.
5M1× seenlast asked 2025 - 7.
What are L1 and L2 regularization methods?
10M1× seenlast asked 2024 - 8.
Explain early stopping, batch normalization, and data augmentation.
10M1× seenlast asked 2023 - 9.
Explain dropout. How does it solve the problem of overfitting?
5M1× seenlast asked 2023
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