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SimCLR Implementation Using PyTorch


Image Classification using Simple Framwork for Contrastive Learning of Visual Representation: This repository is just made for personal learning of PyTorch


Usage

  • Create virtual environment
virtualenv env
  • Activate virtual environment
./env/Scripts/activate
  • Installing dependancies
pip install -r requirements.txt

  • This notebook is written for SimCLR architecture implementation for personal learning
  • Research paper can be found in the repository
  • Dataset used is not from the research paper

Takeaways from Research Paper:

  • Simple Visual Learning: The paper aims to create an easy method for computers to learn from images.
  • Contrastive Learning: It introduces contrastive learning, where the computer learns by comparing similar and different images.
  • Improved Understanding: Through this approach, the computer can better grasp visual patterns and meanings.
  • Applications: The goal is to enhance the computer's visual recognition abilities, benefiting tasks like image recognition and computer vision.

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