sushantag9 Goto Github PK

access_denied

HACK.MOSCOW 3.0

algorithms

Understanding All ▲lgorithms

automated-detction-of-liver-cancer-in-wsi

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

Awesome GAN for Medical Imaging

awesome-mlss

List of summer schools in machine learning + related fields across the globe

c

Implementation of All ▲lgorithms in C Programming Language

chat-bot

chatbot created by CodesBot PSIT

data-science---recommendations-with-ibm

Udacity - Data Science - Term 2 -Recommendations with IBM

datasets

Link to some Awesome Datasets

deep-learming-models

Scripts for Deep Learining models

deepdream

disaster-response-pipeline

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.

disaster-response-pipelines

Part of a Udacity class project on creating an app that classifies disaster response messages.

dog-breed-classifier

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-scripts

Example Machine Learning Scripts for Numerai's Tournament

face-generation

In this project, you'll use generative adversarial networks to generate new images of faces.

famous-research-papers

Links to famous Deep Learning Research Papers

githubgraduation-2021

Join the GitHub Graduation Yearbook and "walk the stage" on June 5.

iitk-no-proxy

No proxy authentication for IITK network

image-compression-and-generation-using-variational-autoencoders-in-python

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.

image-segmentation-keras

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

jupyter

Implementation of All ▲lgorithms in Jupyter Notebook

keras-unet

Implementation of U-Net in Keras

machine-learning

Content for Udacity's Machine Learning curriculum

markdown-resume

The simplest possible resume work flow from markdown source.

minimal

Minimal is a Jekyll theme for GitHub Pages

mlh-localhost-github

This repo contains the source code for the MLH Localhost workshop, How to Collaborate on Code Projects with GitHub.

models

Models and examples built with TensorFlow

multi-container-nginx-react-node-mongo

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.

mysite

Django project