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austin

消息推送平台:pencil: 推送下发【邮件】【短信】【微信服务号】【微信小程序】【企业微信】【钉钉】等消息类型。所使用的技术栈包括：SpringBoot、SpringDataJPA、MySQL、Docker、docker-compose、Kafka、Redis、Apollo、prometheus、Grafana、GrayLog、Flink、Xxl-job、Echarts等等

breast-cancer-classification-using-svm

Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. n the 3-dimensional space is that described in: [K. P. Bennett and O. L. Mangasarian: "Robust Linear Programming Discrimination of Two Linearly Inseparable Sets", Optimization Methods and Software 1, 1992, 23-34]. This database is also available through the UW CS ftp server: ftp ftp.cs.wisc.edu cd math-prog/cpo-dataset/machine-learn/WDBC/ Also can be found on UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29 Attribute Information: 1) ID number 2) Diagnosis (M = malignant, B = benign) 3-32) Ten real-valued features are computed for each cell nucleus: a) radius (mean of distances from center to points on the perimeter) b) texture (standard deviation of gray-scale values) c) perimeter d) area e) smoothness (local variation in radius lengths) f) compactness (perimeter^2 / area - 1.0) g) concavity (severity of concave portions of the contour) h) concave points (number of concave portions of the contour) i) symmetry j) fractal dimension ("coastline approximation" - 1) The mean, standard error and "worst" or largest (mean of the three largest values) of these features were computed for each image, resulting in 30 features. For instance, field 3 is Mean Radius, field 13 is Radius SE, field 23 is Worst Radius. All feature values are recoded with four significant digits. Missing attribute values: none Class distribution: 357 benign, 212 malignant

cbioportal

cBioPortal for Cancer Genomics

flask-adminlte-scaffold_example

flask-adminlte-scaffold是一个Python环境下的WEB后台管理系统脚手架，目标是用极少量的代码，快速构建小型WEB应用。

gcn_traffic_project

ggat

The Gated Graph Attentional Networks (GGAT)

graph_attention_pool

Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)

graphrepur

graphsage

A PyTorch implementation of the paper https://www-cs.stanford.edu/people/jure/pubs/graphsage-nips17.pdf

graphsage-simple

Simple reference implementation of GraphSAGE.

helloflask_example

Hello, Flask!

medfuse

metabric-autoencoder

Extracting High-Quality Features From Biomedical Datasets Using Multimodal Autoencoders

model_log

Model Log 是一款基于 Python3 的轻量级机器学习(Machine Learning)、深度学习(Deep Learning)模型训练评估指标可视化工具，可以记录模型训练过程当中的超参数、Loss、Accuracy、Precision、F1值等，并以曲线图的形式进行展现对比，轻松三步即可实现。

mogcn

Multi-omics integration method using AE and GCN

pe_fusion

predicting-breast-cancer-survival

paper code through layer attention graph convolutional network using multi- dimensional data

pygat

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

selenium-framework

基于 python 的 selenium UI 自动化测试框架，采用 Page Object 设计模式进行二次开发，通过对页面对象和测试代码进行分离，并封装了日志输出，浏览器引擎选择，二次封装常用方法。降低后期因页面变化带来的维护成本，减少了代码的重复，提高测试用例的可读性

sharex

ShareX is a free and open source program that lets you capture or record any area of your screen and share it with a single press of a key. It also allows uploading images, text or other types of files to many supported destinations you can choose from.

tcga_benchmark

TCGA Benchmark Tasks for Clinical Attribute Prediction based on Genome