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bhimrazy/README.md

πŸ‘‹ Hi there, I'm Bhimraj Yadav!

πŸ’» Software Engineer | 🧠 AI Engineer | 🌍 Opensource Contributor | 🌐 Research Enthusiast in Computer Vision & Generative AI

πŸš€ About Me

  • πŸ‘¨πŸ»β€πŸ’» Software Engineer at Fetchly.
  • πŸ‘¨β€πŸ’Ό Studio Publisher & Opensource Contributor at Lightning AI.
  • πŸ’‘ Passionate about leveraging ML and AI to solve real-world problems.
  • πŸ”­ Currently learning and experimenting with deep learning frameworks.
  • 🌱 Always excited to collaborate on projects involving AI, healthcare, and innovative technologies.

🌐 Connect with Me

LinkedIn Twitter Instagram GitHub Facebook

πŸ“§ Email: bhimrajyadav977@gmail.com

🌐 Website: bhimraj.com.np

πŸ“Š GitHub Stats

Github Stats

πŸ› οΈ Technologies & Tools

Python PyTorch Lightning Django FastAPI TypeScript JavaScript React/Next.js AWS CI/CD Docker Git

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πŸ“Ί YouTube Stats

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  1. chat-with-phi-3-vision chat-with-phi-3-vision Public

    Chat with Phi 3.5/3 Vision LLMs. Phi-3.5-vision is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites …

    Jupyter Notebook 32 11

  2. receipt-ocr receipt-ocr Public

    Efficient OCR engine for receipt image processing using Python, FastAPI, and Tesseract

    Python 41 15

  3. unet unet Public

    PyTorchUNet : A PyTorch Implementation of UNet Architecture for Semantic Segmentation of Images from scratch.

    Python 4 1

  4. Image-Recognition-App-using-FastAPI-and-PyTorch Image-Recognition-App-using-FastAPI-and-PyTorch Public

    This is an image recognition application based on the FastAPI framework and PyTorch which uses pretrained DenseNet 121 model to detect the image.

    Jupyter Notebook 25 5

  5. kafka-in-docker-and-python-fastapi kafka-in-docker-and-python-fastapi Public

    Kafka With Python

    Jupyter Notebook 25 8

  6. Lightning-AI/litdata Lightning-AI/litdata Public

    Transform datasets at scale. Optimize datasets for fast AI model training.

    Python 387 47