junmeiW

shap

A unified approach to explain the output of any machine learning model.

statrethinking_winter2019

Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019

Tutorial-Machine-Learning-Based-Survival-Analysis

This repository is tutorial about survival analysis based on advanced machine learning methods including Random Forest, Gradient Boosting Tree and XGBoost. All of them are implemented in R.

AA_program

Including sql codes in AA(Anti-Arrhythmic) program(baeds on eICU database)

deCOOC

model for inferring cell type compositions(proportions)

deepC

A neural network framework for predicting the Hi-C chromatin interactions from megabase scale DNA sequence

echo-mimiciii

Transthoracic echocardiography and mortality in sepsis: analysis of the MIMIC-III database

FYP2017_Reinforcement_learning_dianwen

Guideline-for-Computational-Biology-and-Bioinformatics

HiCSR

HiCSR: a Hi-C super-resolution framework for producing highly realistic contact maps

IABP

IABP project

MCMC

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

mixedmodels-misc

miscellaneous materials for mixed models, mostly in R

pammtools

Piece-wise exponential Additive Mixed Modeling tools

pygcn

Graph Convolutional Networks in PyTorch

SMOTE-Oversample-Rare-Events

Youtube companion (https://www.youtube.com/watch?v=1Mt7EuVJf1A&feature=youtu.be) - Brief introduction to the SMOTE R package to super-sample/ over-sample imbalanced data sets. SMOTE will use bootstrapping and k nearest neighbor to synthetically create additional observations. SMOTE white paper: https://www.jair.org/media/953/live-953-2037-jair.pdf

survival_boost

xgboost for survival data

TensorFlow-Course

Simple and ready-to-use tutorials for TensorFlow

TensorFlow-Examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs

TensorFlow-Tutorials

TensorFlow Tutorials with YouTube Videos