Alternatives and similar repositories for model-based-testing-hypotheses

Users that are interested in model-based-testing-hypotheses are comparing it to the libraries listed below

• RamiKrispin / atsaf
  Applied Time Series Analysis and Forecasting
  ☆169Updated 2 years ago
• EmilHvitfeldt / feature-engineering-az
  Source for book "Feature Engineering A-Z"
  ☆150Updated 2 weeks ago
• JB-Statistical-Consulting / biostatistics
  Biostatistics resources : reading list, RMarkdown notebooks, and more!
  ☆80Updated last month
• einatboro / awesome-survival-analysis
  Resources for Survival Analysis
  ☆98Updated 3 months ago
• RamiKrispin / awesome-ds-setting
  A tutorial for setting a new machine with core data science tools
  ☆295Updated 9 months ago
• RamiKrispin / useR2024-pipeline-workshop
  Materials for the useR!2024 conference workshop "Deploy and Monitor ML Pipelines with R, Open Source, and Free Applications"
  ☆57Updated this week
• RamiKrispin / shinylive
  A guide for deploying Shinylive Python application into Github Pages
  ☆135Updated last year
• RamiKrispin / deploy-flex-actions
  Deploying flexdashboard on Github Pages with Docker and Github Actions
  ☆215Updated last year
• adrianolszewski / Logistic-regression-is-regression
  Despite the popular yet wrong claim that logistic regression "is not a regression", it's one of the key regression and hypothesis testing…
  ☆29Updated 6 months ago
• mguindani / Lectures
  This repository contains slides from some of the classes I have taught in my career. The repository will be updated from time to time. I…
  ☆33Updated 8 months ago
• LSTP-stat / StatResourcesHub
  StatsResourcesHub: Your go-to repository for all things statistics and programming. Find tutorials, code samples, and tips in Python, R,…
  ☆58Updated last year
• aeturrell / python4DS
  Python for Data Science. This repository hosts the code behind the online book that teaches you how to use Python for data science.
  ☆150Updated last month
• robjhyndman / fpp3_slides
  Slides to accompany Forecasting: Principles and Practice, 3rd edition
  ☆75Updated last year
• RamiKrispin / Introduction-to-Docker
  (WIP) Getting started with Docker - An introduction to Docker with data science and engineering applications
  ☆128Updated 2 years ago
• chelseaparlett / CPSC392ParlettPelleriti
  ☆176Updated last year
• jbkunst / klassets
  ☆63Updated 10 months ago
• RamiKrispin / USelectricity
  Forecast the US demand for electricity
  ☆100Updated 3 years ago
• RamiKrispin / vscode-r
  A Tutorial for Setting R Development Environment with VScode, Dev Containers, and Docker
  ☆274Updated last year
• ModelOriented / forester
  Trees are all you need
  ☆112Updated last year
• ewharton / ab-testing-resources
  ☆87Updated last year
• AnttiRask / learning_machine_learning
  I'm learning ML with R. Focusing on (but not limiting myself to) tidyverse and tidymodels.
  ☆16Updated 10 months ago
• rstudio-conf-2022 / people-analytics-rstats
  ☆220Updated 3 years ago
• ostojanovic / causalML
  ☆33Updated last year
• RamiKrispin / ts-cluster-analysis-r
  Materials for the the Analyzing Time Series at Scale with Cluster Analysis in R Workshop
  ☆19Updated 7 months ago
• FJRubio67 / StatisticalInference
  Lecture Notes on Statistical Inference
  ☆77Updated last year
• aml4td / website
  Website sources for Applied Machine Learning for Tabular Data
  ☆150Updated last week
• posit-dev / python-tidytuesday
  ☆93Updated 4 months ago
• eleafeit / ab_test
  Advanced A/B Testing Workshop
  ☆19Updated 4 years ago
• RamiKrispin / ai-dev-2024-ml-workshop
  Materials for the AI Dev 2024 conference workshop "Deploy and Monitor ML Pipelines with Python, Open Source, and Free Applications"
  ☆93Updated this week
• FarrellDay / miceRanger
  miceRanger: Fast Imputation with Random Forests in R
  ☆69Updated 3 years ago