Deep LearningCSC701
11 topics 71 PYQs
Semester 7 · 2019 (C-scheme) · AIML & Data Science
MU-Cortex tracks 71 past-year questions for Deep Learning (CSC701), a semester 7 subject for AIML & Data Science under the 2019 (C-scheme) syllabus. They are grouped below into 11 topics, each question tagged with its marks and how many times it has appeared in papers from 2023–2026. Reading the questions is free; the model answers need an account.
Most repeated topics in CSC701
- Optimization Techniques — 7 questions, asked 11 times in total
- Training Feedforward DNN — 6 questions, asked 10 times in total
- Regularization Methods — 9 questions, asked 10 times in total
- CNN Architecture and Operations — 8 questions, asked 9 times in total
- LSTM and GRU — 8 questions, asked 8 times in total
All topics and questions
Ordered by syllabus module.
Module 1 · Fundamentals of Neural Network
Module 2 · Training, Optimization and Regularization of Deep Neural Network
Module 3 · Autoencoders: Unsupervised Learning
Module 4 · Convolutional Neural Networks (CNN): Supervised Learning
Module 5 · Recurrent Neural Networks (RNN)
Module 6 · Recent Trends and Applications
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