Beast code in Giters

Ellen Wang's repositories

mimic-code

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

MIT100

mimic4ed-benchmark

Python workflow for generating benchmark datasets and machine learning models from the MIMIC-IV-ED database.

GPL-3.0000

citation-tracker

Tools for tracking citations to MIMIC, PhysioNet etc.

MIT000

PH525.1x-Statistics-and-R-for-the-Life-Sciences-HarvardX

PH525.1x: Statistics and R for the Life Sciences HarvardX solutions

000

IntroductionToProbabilityPy

Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition

000

This course will start with the basics, analyzing a large corpus of text documents to discover the structure in the data and how words are put together. It will cover cleaning and analyzing text data, then building and sampling from a predictive text model. Finally, you will use the knowledge you gained in data products to build a predictive text product you can show off to your family, friends, and potential employers.

Language:HTML000

neuronaldynamics-exercises

Python exercises accompanying the book "Neuronal Dynamics"

GPL-2.0000

Course-Project-Shiny-Application-and-Reproducible-Pitch

Language:HTML000

Practical-Machine-Learning-Prediction-Assignment

Practical Machine Learning Prediction Assignment

Language:HTML000

FCND-Estimation-CPP-Solution

Language:Jupyter Notebook000

RepData_PeerAssessment1

Peer Assessment 1 for Reproducible Research

Language:HTML000

ExploratoryDataAnalysisCoursera

Language:R000

datasciencecoursera

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

100