code-cse

code-cse.github.io

personal-portfolio-and-blog

command-installation

Command for different package installation in GPU/CPU

Deep-Learning-in-Production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

Deep-learning-Models

This repository contains the code for various deep learning models and different architecture.

DL-using-Numpy

This repository contains different implementation of deep learning model using Numpy.

Face-Detection-SSD

This repository contains the code for Face detection using SSD.

Mind-Blowing-DSA-Problem

Mind-Blwoing-DSA-Problem is the combination of different Competitive-Programming challenging problem asked by different Compaines and various Coding-Competition.

object-tracking

This repo contains code for object tracking based on centroid value.

SODWTSMFW

Pointer-Generator Network, NLP, Summarization-of-documents-with-title-of-doc-summary-of-doc-and-most-frequent-word

Splice-DNA-Gene

Splice-Gene-Prediction, Healthcare, Medical-science, DNA

code-cse/academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

code-cse/AI-Deep-Learning-Lab-2021

Data, notebooks, and articles associated with the RSNA AI Deep Learning Lab at RSNA 2021

code-cse/awesome-radiology-report-generation

A curated list of radiology report generation (medical report generation) and related areas. :-)

code-cse/Brats21_KAIST_MRI_Lab

Codes and pretrained weights for winning submission of 2021 Brain Tumor Segmentation (BraTS) Challenge

code-cse/CheXbert

Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

code-cse/Chexpert

Top 1 solution of Chexpert

code-cse/chexpertplusplus

Source implementation and pointer to pre-trained models for Chexpert++, a BERT-based approximation to CheXpert for radiology report labeling.

code-cse/clinicalBERT

repository for Publicly Available Clinical BERT Embeddings

code-cse/Data-Preparation

There are lot of things that need to be done on the given dataset before we feed it to the machine, these things come under data preprocessing. In this repository I have tried to explain those things with some examples.

code-cse/deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

code-cse/DPGN

This repository contains the official implementation of DPGN: Distribution Propagation Graph Network for Few-shot Learning.

code-cse/fairseq-image-captioning

Transformer-based image captioning extension for pytorch/fairseq

code-cse/GPT2-Chest-X-Ray-Report-Generation

This is the implementation of the CDGPT2 model mentioned in our paper 'Automated Radiology Report Generation using Conditioned Transformers'

code-cse/graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

code-cse/ifcc

The code of Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation

code-cse/image-gpt

code-cse/kubeflow

Machine Learning Toolkit for Kubernetes

code-cse/Leetcode

🎓Leetcode solutions in Python 📚

code-cse/leetcode-patterns

A curated list of leetcode questions grouped by their common patterns

code-cse/Leetcode-Premium

code-cse/LeetCode-Solutions

🏋️ (Weekly Update) Python / Modern C++ Solutions of All 1955 LeetCode Problems

code-cse/machine-learning-systems-design

A booklet on machine learning systems design with exercises

code-cse/MONAI

AI Toolkit for Healthcare Imaging

code-cse/PaddleDetection

Object detection and instance segmentation toolkit based on PaddlePaddle.

code-cse/R2Gen

code-cse/SegLoss

A collection of loss functions for medical image segmentation

code-cse/torchsample

High-Level Training, Data Augmentation, and Utilities for Pytorch

code-cse/varadbhogayata.github.io

My Portfolio - Personal Website

code-cse/vertex-ai-samples

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

code-cse/X-Ray-Report-Generation

This is the implementation of the 'VSGRU' model mentioned in our paper 'Automated Radiology Report Generation using Conditioned Transformers'.