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Code implementation of computer vision models for practice based on pytorch and einops.

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Deep Learning Fundamentals

I created this repository to deepen my understanding of fundamental models in deep learning. Specifically, I am focusing on computer vision models, including transformers and CNNs, as I use these extensively in my work. Drawing inspiration from Andrej Karpathy and AI-Summer, I strive to write better code by utilizing tools like einops and einsum. This is a long-term project for me, aimed at improving my implementation skills and growing as a machine learning engineer. While I'm not sure who else may benefit from this repository, I am committed to consistently improving and updating it.

Sequential Models

  • Transformer Encoder (Attention is all you need)
  • Transformer Decoder (Attention is all you need)
  • ViT
  • Swin Transformer v1
  • Swin Transformer v2
  • BEiT

CNN Models

  • yolov3
  • UPerNet

Diffusion Models

  • TBD

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Code implementation of computer vision models for practice based on pytorch and einops.

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