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100-days-of-ml-code

100 Days of ML Coding

attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

awesome-convolutional-attention-mechanism-papers

The most influential papers in convolutional attention mechanisms, suitable for image classification, image and video object segmentation and tracking

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

battery_aging

binary_mask_from_json

Making binary mask images from JSON annotation

corona_ct_classification

covid-19

covidglobal

Code & model files for Rahmandad, Lim & Sterman (2020), Estimating the global spread of COVID-19

covidnet-ct

COVID-Net Open Source Initiative - Models for COVID-19 Detection from Chest CT

curated_covid_ct

We built a large lung CT scan dataset for COVID-19 by curating data from 7 different public datasets. These datasets have been publicly used in COVID-19 diagnosis literature and proven their efficiency in deep learning applications. Therefore, the merged dataset is expected to improve the generalization ability of deep learning methods by learning from all these resources together.

datasharing

The Leek group guide to data sharing

ds-first-steps

e3d_lstm

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond

excel-to-pandas-demo

fastbook

Draft of the fastai book

feelvos

FEELVOS implementation in PyTorch; FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

gscnn

Gated-Shape CNN for Semantic Segmentation (ICCV 2019)

hsn

Code for SIGGRAPH paper CNNs on Surfaces using Rotation-Equivariant Features

image

PHP Image Manipulation

image_segmentation

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

indigo

:ramen: Minimalist Jekyll Template

lovaszsoftmax

Code for the Lovász-Softmax loss (CVPR 2018)

machine-learning-project-walkthrough

An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

maftouni.github.io

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

pandas-viz-demo

pandas_jump_start

Pandas is the library one should master for data wrangling and analysis, and to prepare data for machine learning pipeline. This repository is a jump start to Pandas and its most useful functions.

patient_aware_splitter

It is important not to split images of the same patient between the test and train sets to avoid overfitting. This repository splits a sample Covid/Normal classification dataset into test and train sets in a patient aware and stratified manner.

pytorch-generative-adversarial-networks

A very simple generative adversarial network (GAN) in PyTorch

ranet

RANet: Ranking Attention Network for Fast Video Object Segmentation (VOS), ICCV2019