Alternatives and similar repositories for fcmlcode

Users that are interested in fcmlcode are comparing it to the libraries listed below

• cliburn / sta-663-2018
  ☆73Updated 6 years ago
• avehtari / BDA_m_demos
  Bayesian Data Analysis demos for Matlab/Octave
  ☆63Updated 5 years ago
• ajtulloch / Elements-of-Statistical-Learning
  Contains LaTeX, SciPy and R code providing solutions to exercises in Elements of Statistical Learning (Hastie, Tibshirani & Friedman)
  ☆290Updated 11 years ago
• cliburn / sta-663-2016
  STA663 Statistical Computing and Computation, Spring 2016
  ☆87Updated 9 years ago
• djour / PyBRML
  Python Version of BRML toolbox for Bayesian Reasoning and Machine Learning
  ☆163Updated 9 years ago
• cliburn / sta-663-2019
  Course notes for Computational Statistics and Statistical Compuing
  ☆63Updated 6 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆88Updated 6 months ago
• buruzaemon / IntroductionToProbabilityPy
  Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition
  ☆73Updated 6 years ago
• ULAFF / notebooks
  Programming Exercises
  ☆77Updated 10 years ago
• alexsosn / MarslandMLAlgo
  Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.
  ☆150Updated 4 years ago
• gpstuff-dev / gpstuff
  GPstuff - Gaussian process models for Bayesian analysis
  ☆174Updated 2 years ago
• PhDP / mlbop
  Matlab code for S. Theodoridis' "Machine Learning: A Bayesian and Optimization Perspective" (2015).
  ☆68Updated 6 years ago
• vsmolyakov / ml
  machine learning
  ☆39Updated 6 years ago
• hse-aml / bayesian-methods-for-ml
  Materials for "Bayesian Methods for Machine Learning" Coursera MOOC
  ☆134Updated 4 years ago
• twiecki / Bayesian-Modelling-in-Python
  A python tutorial on bayesian modeling techniques (PYMC3)
  ☆20Updated 9 years ago
• ryo0921 / KyotoUx-009x
  ☆12Updated 2 years ago
• anhncs / Probabilistic-Graphical-Models
  Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
  ☆104Updated 12 years ago
• khanhnamle1994 / statistical-learning
  Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course
  ☆258Updated 7 years ago
• NilsWinter / matlab-bayesian-estimation
  Matlab Toolbox for Bayesian Estimation
  ☆44Updated 9 years ago
• fonnesbeck / bayes_tutorial_2019
  Introductory overview of Bayesian inference
  ☆44Updated 6 years ago
• brian-lau / MatlabStan
  Matlab interface to Stan, a package for Bayesian inference
  ☆82Updated 2 years ago
• harvard-ml-courses / cs181-lectures
  ☆38Updated 6 years ago
• ppaquay / IntroStatLearning
  Solutions to exercises from the book "Introduction to Statistical Learning"
  ☆24Updated 10 years ago
• krasserm / machine-learning-notebooks
  Stanford Machine Learning course exercises implemented with scikit-learn
  ☆348Updated 4 years ago
• mscaudill / IntroStatLearn
  Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python.
  ☆105Updated 7 years ago
• twiecki / WhileMyMCMCGentlySamples
  my blog
  ☆268Updated 3 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• rflamary / nonconvex-optimization
  Matlab/Octave toolbox for nonconvex optimization
  ☆50Updated 8 years ago
• yixuan / ADMM
  Solving Statistical Optimization Problems Using the ADMM Algorithm
  ☆75Updated 8 years ago