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megbm

This R package implements some machine learning methods for longitudinal and clustered data based on the standard generalized linear mixed effect model, regression trees, and generalized boosted machines.

mining-the-social-web-2nd-edition

The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

ml-kfoldcrossvalidation

ml-python

ML with Python

mlbook-titanic

মেশিন লার্নিং: হাতে কলমে 'টাইটানিক 'প্রজেক্ট ওয়ার্কবুক

mltraining

মেশিন লার্নিং: হাতে কলমে 'টাইটানিক 'প্রজেক্ট স্ক্রিপ্ট

mtlsa

A Multi-Task Learning Formulation for Survival Analysis

mvtboost

Boosted regression trees for continuous, multivariate responses.

nnet-survival

A Simple Discrete-Time Survival Model for Neural Networks

practicalai

📚 A practical approach to machine learning.

propensityscorematching

with R

pytorch-101-tutorial-series

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

random-survival-forest

A Random Survival Forest implementation for python inspired by Ishwaran et al.

recurrent-neural-networks

Learning about and doing projects with recurrent neural networks

regcox

Coxnet regularization and Active Learning

rfacebook

Dev version of Rfacebook package: Access to Facebook API via R

scikit-learn

scikit-learn: machine learning in Python

scikit-survival

Survival analysis built on top of scikit-learn

sepsis_identification

Early Prediction of Sepsis from Clinical Data: the PhysioNet/Computing in Cardiology Challenge 2019

siamese-competing-risks

Published in ICANN 2018

spoon-knife

This repo is for demonstration purposes only.

subdistdiscsurvival

Supplemental R code and data to 'Subdistribution Hazard Models for Competing Risks in Discrete Time'

subdistribution-beta-stacy

Code for the analyses of the paper "Reinforced urns and the subdistribution beta-Stacy process prior for competing risks analysis" of Arfè, Peluso, and Muliere

supp_material

Supplementary material of the paper ``Direct modelling of the crude probability of cancer death and the number of life-years lost due to cancer without needing the cause of death: a pseudo-observation approach in the relative survival setting''. A step-by-step guide on how to model the pseudo-observations of the crude probability of death and the life-years lost in the relative survival setting.

survutils

Different kinds of functions that can be applied on survival data for prediction

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

tensorflow-survival-analysis

Making survival analysis work in TensorFlow

tensorflow2

TensorFlow 2.0 Google Colab Notebook

tfdeepsurv

COX Proportional risk model and survival analysis implemented by tensorflow.