Unsupervised representation learning by predicting image rotations on MNIST

This project implements a deep learning project.

File Structure

• models/: Directory containing trained models
• .gitignore: Configuration for Git to ignore specific files and directories
• README.md: This file, containing project information
• RotNetV_any.ipynb: Jupyter notebook for RotNet implementation
• batch_corrected.ipynb: Jupyter notebook with corrected batch processing
• dataset.py: Python script for dataset handling and image transformations
• helper_functions.py: Utility functions for the project
• models.py: Definition of neural network models
• paper_notes.md: Notes on the research paper related to this project
• projet_deep.ipynb: Jupyter notebook containing the project's deep learning implementation
• train_baseline.ipynb: Jupyter notebook for training the baseline model

Getting Started

To get started with this project:

1. Clone the repository
2. Install the required dependencies (list them here or refer to a requirements.txt file)
3. Run the Jupyter notebooks in the following order:
   • train_baseline.ipynb
   • RotNetV_any.ipynb