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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

shap

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

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

statrethinking_winter2019

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

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

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.