Alternatives and similar repositories for ProbAndStats-PyDataNYC2019:

Users that are interested in ProbAndStats-PyDataNYC2019 are comparing it to the libraries listed below

• gbosquechacon / statrethink_course_in_pymc3
  Statistical Rethinking course in pymc3
  ☆143Updated 4 years ago
• bambinos / educational-resources
  Educational resources
  ☆104Updated 3 years ago
• AllenDowney / SurvivalAnalysisPython
  Explorations of survival analysis in Python
  ☆50Updated 2 years ago
• corriebar / Bayesian-Workflow-with-PyMC
  Repository with code, notebook and slides for my talk at PyConDE & PyData Berlin 2019
  ☆36Updated 2 years ago
• AllenDowney / BiteSizeBayes
  An introduction to Bayesian statistics using Python and (coming soon) R.
  ☆130Updated last year
• springcoil / probabilisticprogrammingprimer
  ☆90Updated 4 years ago
• eigenfoo / tests-as-linear
  Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
  ☆90Updated 7 months ago
• ericmjl / causality
  In which I play with the ideas surrounding causality
  ☆51Updated 2 years ago
• tdpetrou / Minimally-Sufficient-Pandas
  There are always multiple ways to complete a task in Pandas. A minimal subset of the library is sufficient for almost everything.
  ☆83Updated 2 years ago
• betanalpha / jupyter_case_studies
  Inference case studies in jupyter
  ☆93Updated 6 years ago
• AlexIoannides / pymc-example-project
  Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
  ☆105Updated 6 years ago
• AmpersandTV / pymc3-hmm
  Hidden Markov models in PyMC3
  ☆99Updated last year
• fonnesbeck / Bayes_Computing_Course
  ☆230Updated 3 years ago
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆40Updated 2 years ago
• canyon289 / bayesian-model-evaluation
  Presented at Scipy Conference 2019
  ☆125Updated 5 years ago
• CamDavidsonPilon / PyDataNY_2019_tutorial
  Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference
  ☆25Updated 5 years ago
• AM207 / 2018fall
  ☆37Updated 4 years ago
• COGS108 / Readings
  A curated list of suggested reading materials.
  ☆19Updated 5 months ago
• amueller / ml-workshop-3-of-4
  Advanced Machine Learning with Scikit-learn part I
  ☆142Updated 4 years ago
• klemag / pydataLDN_2019-maintainable-code-for-data-science
  ☆47Updated 5 years ago
• hyosubkim / bayes-toolbox
  bayes-toolbox
  ☆93Updated 3 months ago
• statsthinking21 / statsthinking21-python
  Python companion for Statistical Thinking in the 21st Century
  ☆72Updated 5 months ago
• amueller / ml-workshop-1-of-4
  Introduction to Machine learning with Python, 4h interactive workshop
  ☆310Updated 4 years ago
• amueller / aml
  Applied Machine Learning with Python
  ☆78Updated 11 months ago
• junpenglao / All-that-likelihood-with-PyMC3
  ☆72Updated 6 years ago
• TomAugspurger / pydata-nyc-ph2t
  PyData NYC 2017: Pandas Head to Tail
  ☆57Updated 7 years ago
• brianspiering / nlp-course
  An introduction to Natural Language Processing (NLP) course
  ☆39Updated 3 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆42Updated last year
• junpenglao / PrecisionWorkshop1_Prep
  Preparation materials for CEAi Precision Workshop #1 on Bayesian modelling
  ☆57Updated 6 years ago
• ContextLab / storytelling-with-data
  Course materials for Dartmouth Course: Storytelling with Data (PSYC 81.09).
  ☆105Updated last year