Alternatives and similar repositories for Study-of-David-Mackay-s-book-

Users that are interested in Study-of-David-Mackay-s-book- are comparing it to the libraries listed below

• hse-aml / bayesian-methods-for-ml
  Materials for "Bayesian Methods for Machine Learning" Coursera MOOC
  ☆135Updated 4 years ago
• glouppe / info8004-advanced-machine-learning
  Lectures for INFO8004 Advanced Machine Learning, ULiège
  ☆113Updated 4 months ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆129Updated 5 years ago
• cliburn / sta-663-2018
  ☆73Updated 6 years ago
• tensorchiefs / dl_book
  legend
  ☆206Updated last year
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆95Updated 2 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• alexsosn / MarslandMLAlgo
  Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.
  ☆148Updated 4 years ago
• kevinzakka / learn-linalg
  Learning some numerical linear algebra.
  ☆70Updated 4 years ago
• cranmer / stats-ds-book
  http://cranmer.github.io/stats-ds-book
  ☆73Updated 4 years ago
• fastai / numerical-linear-algebra-v2
  Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program
  ☆275Updated 7 years ago
• mlss-2019 / tutorials
  ☆275Updated 5 years ago
• buruzaemon / IntroductionToProbabilityPy
  Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition
  ☆74Updated 6 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆188Updated 4 years ago
• ericmjl / bayesian-deep-learning-demystified
  In which I try to demystify the fundamental concepts behind Bayesian deep learning.
  ☆123Updated 7 years ago
• springer-math / dynamical-systems-with-applications-using-python
  Source code for 'Dynamical Systems with Applications Using Python' by Stephen Lynch
  ☆154Updated 7 years ago
• mohd-faizy / Probabilistic-Deep-Learning-with-TensorFlow
  Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of…
  ☆68Updated 8 months ago
• snowdj / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆88Updated 6 years ago
• cliburn / sta-663-2019
  Course notes for Computational Statistics and Statistical Compuing
  ☆63Updated 6 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• probml / probml-notebooks
  Notebooks for "Probabilistic Machine Learning" book
  ☆203Updated 3 years ago
• ericmjl / dl-workshop
  Crash course to master gradient-based machine learning. Also secretly a JAX course in disguise!
  ☆227Updated last year
• kojino / Harvard-Robust-Machine-Learning
  Repository for CS282R: Robust Machine Learning at Harvard University.
  ☆73Updated 7 years ago
• rlabbe / tutorials
  tutorials that may or may not turn into a book
  ☆48Updated 5 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆168Updated 2 years ago
• RobertTLange / reading-notes-ml
  Progress, Notes, Summaries and a lot of Questions on Machine Learning
  ☆55Updated 5 years ago
• AllenDowney / ComplexityScience
  Repository for a workshop on Complexity Science
  ☆39Updated 3 years ago
• AM207 / 2018fall
  ☆38Updated 4 years ago
• MauroCE / PythonBRMLtoolbox
  Python 3.7 version of David Barber's MATLAB BRMLtoolbox
  ☆25Updated 6 years ago
• eth-cscs / abcpy
  ABCpy package
  ☆115Updated last year