Sushant Agarwal's Projects
HACK.MOSCOW 3.0
Understanding All ▲lgorithms
This project focuses on detection and segmentation of liver cancer in WSI using parallel processing on GPU and used techniques of pruning to improve and optimize my model. The baseline of the model is Unet and Vnet. Further the model has been upgraded with a ResNet backbone and model pruning technique were also applied.
Awesome GAN for Medical Imaging
List of summer schools in machine learning + related fields across the globe
Implementation of All ▲lgorithms in C Programming Language
chatbot created by CodesBot PSIT
Udacity - Data Science - Term 2 -Recommendations with IBM
Link to some Awesome Datasets
Scripts for Deep Learining models
In this project, you'll apply these skills to analyze disaster data from Figure Eight to build a model for an API that classifies disaster messages.
Part of a Udacity class project on creating an app that classifies disaster response messages.
Given an image of a dog, your algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed
Example Machine Learning Scripts for Numerai's Tournament
In this project, you'll use generative adversarial networks to generate new images of faces.
Links to famous Deep Learning Research Papers
Join the GitHub Graduation Yearbook and "walk the stage" on June 5.
No proxy authentication for IITK network
This project will introduce the Variational Autoencoder. I will discuss some basic theory behind this model, and move on to creating a machine learning project based on this architecture. Our data comprises 60.000 characters from a dataset of fonts. We will train a variational autoencoder that will be capable of compressing this character font data from 2500 dimensions down to 32 dimensions. This same model will be able to then reconstruct its original input with high fidelity. The true advantage of the variational autoencoder is its ability to create new outputs that come from distributions that closely follow its training data: we can output characters in brand new fonts.
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
Implementation of All ▲lgorithms in Jupyter Notebook
Implementation of U-Net in Keras
Content for Udacity's Machine Learning curriculum
The simplest possible resume work flow from markdown source.
Minimal is a Jekyll theme for GitHub Pages
This repo contains the source code for the MLH Localhost workshop, How to Collaborate on Code Projects with GitHub.
Models and examples built with TensorFlow
Multi container application with Nginx, React, Node and Mongo DB. This repository also contains Terraform IaC (Infrastructure as Code) for a CICD pipeline to build and push images to DockerHub.
Django project