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Hello, Waving hand animated gif I'm Akshay Dongare

AkshayDongare

šŸ’« About Me :

  • šŸŒ± Iā€™m an undergraduate student currently learning more about Deep Learning.
  • šŸ’¬ Ask me about AI/ML or any tech-related stuff.
  • šŸ“« How to reach me: https://linktr.ee/akshaydongare

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Tensorflow Python C++ JavaScript Google-Cloud MongoDB HTML5 MySQL Canva Linux Windows

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Akshay Dongare's Projects

docker-local-development icon docker-local-development

A repo to show how to use Docker for making an isolated, local, development environment for python and running a streamlit app in it

dsbda_mini_project icon dsbda_mini_project

This application is streamlit dashboard that can be used to analyze motor vehicle collision in NYC

error-cpp-build-tools icon error-cpp-build-tools

error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/

gconsft2023 icon gconsft2023

I presented a paper at the Global Conference on Sustainable and Futuristic Technologies 2023 (GConSFT2023) organised by Marathwada Mitra Mandal's College of Engineering Pune on 14 December 2023 in the Computational Technologies track.

ipv6-server icon ipv6-server

Self Host your website using HTML and ipv6. Use your laptop as host to display your HTML website to the internet using IPV6 protocol. Each device has a unique IPV6 address (correlated to device's MAC address) which makes it possible to host and share websites over the internet without the need of port forwarding like in ipv4!)

lane-segmentation-along-with-traffic-sign-detection icon lane-segmentation-along-with-traffic-sign-detection

Performed real-time semantic segmentation for lane detection combined with traffic sign recognition on a video stream. Trained Faster R-CNN and Resnet50 on the GTSRB dataset for traffic sign recognition and trained an FCN on custom dataset for lane segmentation

mnist-fashion-classification icon mnist-fashion-classification

Multi-class classification on MNIST Fashion dataset which has 10 classes (fasion items like bag, boot, top etc). It has 28x28 pixel grayscale images.

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