📘 Course Overview:
This repository contains my coursework (assignments, & semester exams) for the Deep Learning course at IIIT Delhi in Winter 2025.
The course covers foundational to advanced topics including MLPs, CNNs, Autoencoders (vanilla & variational), GANs, RNNs (LSTM), Attention & Transformers, model interpretability (saliency/sensitivity maps), auto-regressive models, and model compression techniques.
📂 Folder Structure:
/Assignment 1: Implemented MLPs and CNNs (with custom Inception blocks) for Fashion MNIST and Speech Commands classification./Assignment 2: Built Autoencoders, VAEs, and CVAEs for latent space modeling on Fashion MNIST./Assignment 3: Designed and trained a conditional GAN to generate flower images based on textual descriptions./Assignment 4: Predicted stock prices using LSTM-based time series modeling./Kaggle Competition 1: Developed a regression model to minimize MSE on a structured dataset with three integer inputs./Kaggle Competition 2: Build a DL model to decode EEG signals into intended speech and generate corresponding spectrograms. Not Attempted./Quizzes: Contains materials related to the quizzes./Midsem: Contains materials related to the midterm examination./Endsem: Contains materials related to the endterm examination.
📅 Semester: 6th Semester (3rd Year)
📚 Course Details:
Instructor's name - Vinayak Abrol (abrol@iiitd.ac.in)
Course Code - CSE641
📌 Important: Please make sure to follow the guidelines and policies outlined by the institution regarding the use of shared coursework materials. Use this repository responsibly and avoid any violations of academic integrity. Codes are provided for reference purposes only. It's recommended to understand the codes and implement them independently.