shark8me / Building_Probabilistic_Graphical_Models_in_Python

Related projects ⓘ

Alternatives and complementary repositories for Building_Probabilistic_Graphical_Models_in_Python

• ericmjl / bayesian-stats-talk
  Doing Bayesian statistics in Python!
  ☆66Updated 6 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆67Updated 5 years ago
• rlabbe / statistical-rethinking
  Notebooks containing R code from Richard McElreath's Statistical Rethinking
  ☆73Updated 8 years ago
• paulperry / kaggle
  Kaggle competition results
  ☆20Updated 5 years ago
• yandexdataschool / MLatGradDays
  Course of Machine Learning in Science and Industry at Heidelberg university
  ☆47Updated 7 years ago
• fonnesbeck / multilevel_modeling
  Tutorial on multilevel modeling, using Gelman radon example
  ☆55Updated 9 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 6 years ago
• parsing-science / pymc3_quickstart_guide
  ☆80Updated 8 years ago
• RJT1990 / PyData2016-SanFrancisco
  A Tour of Time Series Analysis
  ☆23Updated 8 years ago
• adrowan / PyDataLondon2017
  Bayesian Deep Learning with Edward (and a trick using Dropout)
  ☆15Updated 7 years ago
• kuleshov / cs228-notes
  Lecture notes on probabilistic graphical modeling, based on Stanford CS228 (work in progress!)
  ☆30Updated 7 years ago
• aflaxman / pymc-examples
  PyMC Example Notebooks
  ☆75Updated 10 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆90Updated 4 years ago
• bikestra / bdapy
  Reproducing plots of Bayesian Data Analysis (Gelman et al, 3rd Edition) in Python
  ☆45Updated 9 years ago
• gapatino / Making-Your-Code-Faster-Cython-and-parallel-processing-in-the-Jupyter-Notebook
  Jupyter Notebook for PyData DC 2016 on "Making Your Code Faster: Cython and parallel processing in the Jupyter Notebook"
  ☆12Updated 7 years ago
• fabianp / overview_optalgs
  ☆29Updated 4 years ago
• inf16nyu / home
  ☆78Updated 7 years ago
• PacktPublishing / Large-Scale-Machine-Learning-With-Python
  Code repository for Large Scale Machine Learning with Python, published by Packt
  ☆87Updated last year
• civisanalytics / muffnn
  Multilayer Feed-Forward Neural Network predictive model implementations with TensorFlow and scikit-learn
  ☆45Updated last year
• gpschool / gpss17
  Gaussian Process and Uncertainty Quantification Summer School 2017
  ☆26Updated last year
• springcoil / probabilisticprogrammingprimer
  ☆91Updated 3 years ago
• amueller / talks_odt
  Slides and materials for most of my talks by year
  ☆91Updated last year
• jfsantos / keras-tutorial
  Tutorial teaching the basics of Keras and some deep learning concepts
  ☆104Updated 7 years ago
• lmc2179 / bayesian_bootstrap
  bayesian bootstrapping in python
  ☆121Updated 2 years ago
• rasbt / pydata-annarbor2017-dl-tutorial
  Code snippets for "Introduction to Deep Learning with TensorFlow" at PyData Ann Arbor Aug 2017
  ☆79Updated 7 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆59Updated 7 years ago
• uvadlc / uvadlc_practicals_2016
  Repository for practical assignments for UvA Deep Learning Course 2016
  ☆51Updated 7 years ago
• fonnesbeck / bayes_tutorial_2019
  Introductory overview of Bayesian inference
  ☆45Updated 5 years ago