Michael's GitHub Space
I'm Michael, and I do all manner of things within the realm of data science. Here you'll find source code for modeling, packages, general programming, and various other things.
Name: Michael Clark
Type: User
Company: Senior Machine Learning Scientist @strongio
Bio: Statistical Philosopher, Brute Empiricist, Model Gallivanter
Twitter: statsdatasci
Location: Ann Arbor
Some thoughts, particularly for graduate students, but any researcher in applied disciplines on what they can do regarding statistical and programming basics to make their research efforts more efficient.
a look at the big 4
:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
Raw files for a document that will serve as a reference for dealing with 'big' data in R.
Spells for everyday living. (also a book coming out in 2024)
Authoring Books and Technical Documents with R Markdown
bookdown starter set
analytical bayesian t-test
Raw files for a document that provides an overview of models for the case of a categorical dependent variable.
Raw files for a document covering different approaches to dealing with dependent data.
gitignore, css, etc.
Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯
connections among various statistical methods
Raw files for a summary of various measures of dependency.
Set of slides for a workshop introducing dplyr related functionality, piping and related.
This document forms the basis of several workshops/talks that get into everyday programming with R, but also includes mirrored code in Python as Jupyter notebooks.
Datasets I used at some point.
This will introduce R users to the Distill format for R Markdown, for scientific communication and building websites.
Documents that go into methodological detail regarding various statistical procedures.
Workshop to introduce participants to rstanarm and brms.
A survey of tools that make EDA more automated.
Raw files for a document covering techniques for speeding up R, especially before parallelization.
Get football club rankings from 538
⚽ golazo!
Functions for using mgcv for mixed models. 📈
A document introducing generalized additive models.📈
A workshop on using generalized additive models and the mgcv package.
Visualizing correlation matrix structure.
A document covering machine learning basics. 🤖📊
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.