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Hi šŸ‘‹, I'm Bhargav

A Software Engineer with Expertise in Machine Learning Research and Operations šŸ‡®šŸ‡³

GIF

  • šŸ”­ Iā€™m currently working as Jr. Staff AI Engineer at Detect Technologies
  • šŸ“ I regularly write articles on medium@callbhargavp
  • šŸ˜„ I graduated from Ahmedabad University in 2021 with a degree in Information and Communication Technology.
  • šŸŒ± I work with technologies such as Tensorflow Extended, Python, Docker, Kubernetes, AWS.
  • šŸŒ± Iā€™m curious about Artificial Intelligence, Machine Learning Operations, and Green Technology.
  • šŸ“« How to reach me [email protected]
  • šŸ“„ Know about my experiences Resume

Connect with me šŸ¤

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Engineer1999

Ā Engineer1999

Bhargav Patel's Projects

a-curated-list-of-ml-system-design-case-studies icon a-curated-list-of-ml-system-design-case-studies

This repository contains a curated collection of 300 case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are organized to help you easily find relevant case studies based on industry or specific ML use cases.

aima-python icon aima-python

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

air-bird icon air-bird

This mobile application is useful to monitor the dynamic pollution sources integrated with google map API.

autoencoder_for_physical_layer icon autoencoder_for_physical_layer

This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

chest-x-ray-classification-with-gradcam icon chest-x-ray-classification-with-gradcam

Achieved 96.7% classification accuracy using transfer learning approach with VGG16 pre-trained model. We utilized Gradient based Class Activation Maps (GradCAM) to provide transparency for the decision taken by CNN classifier.

convolutional-neural-network icon convolutional-neural-network

I have use Convolutional Neural Network to make a classification model for Fashion MNIST data set. After 200 epoch model has achieved 96.9% of validation Accuracy.

covid-net icon covid-net

COVID-Net model for COVID-19 detection on COVIDx dataset

cs229-2018-autumn icon cs229-2018-autumn

All notes and materials for the CS229: Machine Learning course by Stanford University

deblurgan icon deblurgan

Image Deblurring using Generative Adversarial Networks

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