Discover fonnesbeck/Bios6301 Open Source project

Recent builds of Numpy, Scipy, Matplotlib, iPython and PyMC for OSX

534

ScipySuperpack

Shell

490

scipy2014_tutorial

Tutorial: Bayesian Statistical Analysis in Python

313

Bayes_Computing_Course

Introduction to Statistical Modeling with Python (PyCon 2017)

230

intro_stat_modeling_2017

A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)

167

gp_regression

PyData London 2019 Tutorial on Markov chain Monte Carlo with PyMC3

164

mcmc_pydata_london_2019

PyTennessee 2014: Statistical Data Analysis in Python

153

pytenn2014_tutorial

PyMC3_DataScienceLA

PyMC3 tutorial for DataScience LA (January 2017)

PyData London 2022 Tutorial

probabilistic_python

Tutorial on multilevel modeling, using Gelman radon example

multilevel_modeling

Bayesian Modeling using Stan in R (May/June 2016)

stan_workshop_2016

Computational Statistics II Tutorial at SciPy 2015

scipy2015_tutorial

Introductory overview of Bayesian inference

bayes_tutorial_2019

Probabilistic programming in Python workshop at Oslo universitetssykehus HF

PyMC3_Oslo

Probabilistic Programming and Bayesian Computing with PyMC

bayes_course_2022

PyMC Tutorial for SciPy 2011

pymc_tutorial

A Primer on Python for Statistical Programming and Data Science

enar_2019_tutorial

iPython notebook for Computational Methods for Data Analysis course on Coursera

ComputationalMethodsCourse

bayes_course_dec_2023

Probabilistic Programming and Bayesian Computing with PyMC

Course in Probabilistic Programming in Python for the 2018 EU Summer School

PyMC3_EUSS

Course materials for short course on Bayesian computation

bayes_course_july2020

Python data analysis course for 2017 NGCM Summer Academy

ngcm_pandas_2017

Probabilistic Programming and Bayesian Computing with PyMC

bayes_pydata_london_2024

scikit-learn course for 2017 NGCM Summer Academy

ngcm_sklearn_2017

Scientific Python Programming Workshop, April 2016 Australia

scientific-python-workshop

Developing Hierarchical Models for Sports Analytics

hierarchical_models_sports_analytics

PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3

gp_tutorial_pydata

Python data analysis course for 2015 NGCM Summer Academy

ngcm_pandas_course

Probabilistic Programming and Bayesian Computing with PyMC

bayes_course_june_2024

Implementing Hastie and Tibshirani's Course in Python

StatisticalLearningInPython

bayesian_mixer_london_2017

Fitting Gaussian process models in PyMC3: Bayesian Mixer London 2017 seminar

PyMC3 implementation of Drew Linzer’s dynamic Bayesian election forecasting model

election_pycast

One-day workshop on probabilistic programming with PyMC

pymc_workshop

Markov Decision Processes and Dynamic Optimization module at NCTC, March 2015

NCTC_course

A short introductory workshop on Pandas for applied users

intro_to_pandas

A comparison of Gaussian process fitting packages in Python

gp_showdown

Jupyter for Reproducible Research

jupyter_for_reproducible_research

London Bayes Mixer presentation, June 2023

bayes_mixer_2023

2018 CQS Summer Institute course in machine learning

cqs_machine_learning

Deep Q-learning for Disease Outbreak Decision Modeling

dqn_rl_outbreak_response

SDSS 2024 Course: Probabilistic Programming and Bayesian Computing with PyMC

pymc_sdss_2024

Baseball data analysis in Python

baseball

Basic Bayesian analysis for comparing two groups with continuous and binary outcomes

basic_bayes

Quick tutorial on neural networks and TensorFlow

tensorflow_demo

Slides for SWC git lecture

git_tutorial

useRshootout

useR session on comparing statistical computing languages

bmi_python_tutorial

Brief Python tutorial for Vanderbilt Biomedical Informatics big data class

Functions for calculating the Framingham Risk Score (FRS)

framingham_risk

Outcomes in Children with Bilateral Cochlear implants and Bimodal Hearing

bimodal-bilateral

plotly_bayes

Bayesian analysis for Python with Plotly graphics

bayesball

Probabilistic models for the analysis of baseball data

fonnesbeck.github.io

Strong Inference website

HTML

bayes_course_dec_2024

Probabilistic Programming and Bayesian Computing with PyMC

Python data analysis course for 2016 NGCM Summer Academy

ngcm_pandas_2016

Development of shipping lanes recommendations for Port of Charleston based on right whale activity

CharlestonLanesAnalysis

HTML

ebola_data_processing

Example of importing and cleaning external data

Python files for Vanderbilt University Software Carpentry Bootcamp

bootcamp_python

Meta-analysis of Autism Intervention Effectiveness

autism_intervention_MA

VUMC Seminar Series talk, October 2018

dbmi_seminar_2018

HealthPolicyPython

Python programming workshop for Vanderbilt's Department of Health Policy, December 16, 2015

Docker containers for serving up Jupyter

jupyter-ds

Dockerfile

disruptive_behavior_disorder_MA

Meta-analysis of psychosocial interventions for disruptive behavior disorder (DBD)

CDRN_Obesity

Mid-south CDRN Obesity Project

Decision Analysis Tools Course (March 2015)

SDM_Tools

bayesian_marcel

Bayesian implementation of Tango's MARCEL projection system

PyMC's Big Adventure (MLOSS Workshop 2018)

neurips_2018_talk

Pelican CMS for Strong Inference

stronginference

Makefile

python_and_r

Draft book chapters

git_training

Training repository for Bios301 students

autism_screening

Meta-analysis of autism screening tools

PKUMetaAnalysis

Vanderbilt EPC meta-analysis on PKU supplementary materials

TeX

pmi_example

Example models for Precision Medicine Initiative planning

Mindfulness-based stress reduction (MBSR) intervention study for autism outcomes

mbsr_intervention_study

SDSS 2024 Course: Probabilistic Programming and Bayesian Computing with PyMC

sdss_2024_course

AHRQ_Complex_Interventions

AHRQ Tools for Systematic Reviews of Complex Interventions (Bayesian Inference)

Support materials for CCASAnet's R short course

CCASAnetRCourse

mongolia_measles

Mongolia measles outbreak intervention modeling