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Machine Learning Assignments

This repository contains the implementation of two assignments focusing on various deep learning models, including CNNs, ResNet, RNNs, LSTMs, and Conditional GANs.


Assignment 1: CNN and ResNet Models

Tasks:

  1. Fashion MNIST Classification:

    • Classify Fashion MNIST images into 3 categories: clothes, shoes, and others.
    • Use a custom CNN model.
  2. Emotion Detection:

    • Train and fine-tune a ResNet-18 model for emotion detection:
      • From scratch: Train the ResNet-18 model with random initialization.
      • Fine-tuning: Use a pretrained ResNet-18 model for improved performance.

Objectives:

  • Compare the performance of models trained from scratch vs. fine-tuned.
  • Analyze classification accuracy and example predictions.

Assignment 2: SMS Spam Classification and Fashion MNIST cGAN

Tasks:

  1. SMS Spam Classification & SMS completion:

    • Models:
      • RNN-based Classifier
      • LSTM-based Classifier
    • Objective: Compare the performance of RNN and LSTM models with a similar number of parameters. Provide example results.
  2. Fashion MNIST Conditional GAN:

    • Model: Conditional GAN (cGAN):
      • Generator: Produces images based on a latent code and class label.
      • Discriminator: Classifies (Image, Label) pairs as real or fake.
    • Objective: Generate high-quality images for all 10 classes and showcase 4 examples per class.