janweeee / unsupervisedlearning

Unsupervised Learning Practicals Repository

Welcome to the unsupervisedLearning repository! This repository contains practical implementations of various unsupervised learning models. Below is an overview of the practicals along with instructions on how to navigate the repository.

1. Next Word Prediction with Markov Model

• Dataset: [eminem_songs_lyrics.txt]
• File: markov_next_word_prediction.ipynb

2. Paragraph Generation with Markov Model

• Dataset: [eminem_songs_lyrics.txt]
• File: markov_paragraph_generation.ipynb

3. Discriminator Model for Functions of Two Variables

• File: discriminator_function_model.ipynb

4. Generative Adversarial Network (GAN)

• File: gan_implementation.ipynb

5. GAN for MNIST Dataset

• File: gan_mnist_implementation.ipynb

6. Autoencoder Implementation and Comparison

• a. Vanilla Autoencoder: vanilla_autoencoder.ipynb
• b. Deep Autoencoder: deep_autoencoder.ipynb
• c. Convolutional Autoencoder: convolutional_autoencoder.ipynb
• d. Results Comparison: autoencoder_comparison.ipynb

7. Variational Autoencoder Implementation and Comparison

• a. Implementation on MNIST, Fashion MNIST, and CIFAR10: variational_autoencoder.ipynb
• b. Results Comparison: vae_comparison.ipynb

8. Autoencoder Implementation Fashion(Myntra dataset)

Feel free to explore each practical's notebook for detailed implementations and comparisons. If you have any questions or suggestions, please don't hesitate to reach out.

Happy learning!