410251: Deep Learning
This repository gathers comprehensive material for the SPPU Computer Engineering Deep Learning course (2019 pattern). It includes PYQs with solutions, codes, assignment handouts, write-ups, and explanatory notes to reinforce theory and practice in neural networks, CNNs, RNNs, deep generative models, and reinforcement learning. Ideal for exam prep, project work, and self-study, it provides structured, ready-to-use resources aligned with course outcomes and objectives.
Index
Notes
Codes
- Code-1 (Linear Regression using Deep Neural Network)
- Code-2b (Classification using Deep Neural Network)
- Code-3a (Convolutional Neural Network - Plant Diseases)
- Code-3b (Convolutional Neural Network - MNIST Fashion Dataset)
- Code-4 (Recurrent Neural Network - Google Stock Price Dataset)
Jupyter Notebooks
- Notebook-1 (Linear Regression using Deep Neural Network)
- Notebook-2b (Classification using Deep Neural Network)
- Notebook-3a (Convolutional Neural Network - Plant Diseases)
- Notebook-3b (Convolutional Neural Network - MNIST Fashion Dataset)
- Notebook-4 (Recurrent Neural Network - Google Stock Price Dataset)
Datasets
- Dataset for Practical-1 (Boston House Price)
- Dataset for Practical-2b (IMDB Reviews)
- Dataset for Practical-3b (MNIST Fashion)
- Dataset for Practical-4 (Google Stock Price)
Assignments
- Questions - Assignment 1 and 2
- Assignment-2:
Codes
Practical
Question Papers
IN-SEM PYQ Answers
Question Bank
Miscellaneous
-> Disclaimer: Please read the DISCLAIMER file for important information regarding the contents of this repository.
-> Note: Content such as codes, softcopies, write-ups and question papers is provided by us, i.e. our contributors. You are free to use this content however you wish, without any restrictions. Some of the notes and handouts have been provided by our professors, thus to use them for anything other than educational purposes, please contact them.
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-> Keywords:
SPPU, Savitribai Phule Pune University, Pune University, Computer Engineering, COMP, Fourth Year, Final Year, BE, Semester 8, SEM-8, Notes, Codes, Practical work, Handouts, Assignments, PYQs, deep learning, neural networks, CNN, RNN, reinforcement learning, deep generative models, PYQ solutions, write-ups, SPPU, computer engineering,
