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bigdata-learning

大数据学习记录

cgcnn

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

discovery_precision

Code for paper：Model efficiency: a new metric for evaluating explorative power of machine learning model for materials discovery

drawfigureforpaper

Some python scripts for drawing figures in scientific papers

fatigue-life-prediction-of-aluminum-alloy

flask

fluent_python

gitskills

helloflask

《Flask Web 开发实战》Meta 仓库

hyperparameter-optimization

Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms

kmfcv

K-fold-m-step forward cross-validation is a new approach of evaluating extrapolation performance in materials property prediction.

learngit

used learn git

lgcn

Source code for WWW 2021 paper "Lorentzian Graph Convolutional Networks"

matdeeplearn

MatDeepLearn, package for graph neural networks in materials chemistry

megnet

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

ml-react-app-template

This is a template for creating a Machine Learning application with its front-end developed using React which interacts with a Flask service as the back-end and makes predictions.

mof_pred

mt-cgcnn

NeurIPS 2018 MLMM Workshop: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction

python

pythondatasciencehandbook

used-book-pro

微信小程序云开发校园二手书商城，可在线支付提现，源码全开源

util