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

• cliburn / sta-663-2018
  ☆73Updated 6 years ago
• glouppe / info8004-advanced-machine-learning
  Lectures for INFO8004 Advanced Machine Learning, ULiège
  ☆114Updated 7 months ago
• hse-aml / bayesian-methods-for-ml
  Materials for "Bayesian Methods for Machine Learning" Coursera MOOC
  ☆136Updated 5 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆129Updated 5 years ago
• tensorchiefs / dl_book
  legend
  ☆209Updated 2 years ago
• mlss-2019 / tutorials
  ☆276Updated 5 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆90Updated last week
• 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…
  ☆70Updated last month
• springer-math / dynamical-systems-with-applications-using-python
  Source code for 'Dynamical Systems with Applications Using Python' by Stephen Lynch
  ☆154Updated 7 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
• kevinzakka / learn-linalg
  Learning some numerical linear algebra.
  ☆70Updated 4 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• cliburn / sta-663-2019
  Course notes for Computational Statistics and Statistical Compuing
  ☆63Updated 6 years ago
• ericmjl / bayesian-deep-learning-demystified
  In which I try to demystify the fundamental concepts behind Bayesian deep learning.
  ☆123Updated 7 years ago
• alexsosn / MarslandMLAlgo
  Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.
  ☆149Updated 4 years ago
• cranmer / stats-ds-book
  http://cranmer.github.io/stats-ds-book
  ☆73Updated 4 years ago
• ksachdeva / rethinking-tensorflow-probability
  Statistical Rethinking (2nd Ed) with Tensorflow Probability
  ☆272Updated 3 years ago
• leopd / geometric-intuition
  Understanding ML and deep learning through geometry
  ☆157Updated 3 years ago
• PacktPublishing / Bayesian-Analysis-with-Python-Second-Edition
  Bayesian Analysis with Python - Second Edition, published by Packt
  ☆135Updated 4 years ago
• AaltoML / SDE
  Example codes for the book Applied Stochastic Differential Equations
  ☆198Updated this week
• snowdj / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆89Updated 6 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆278Updated 6 years ago
• fastai / numerical-linear-algebra-v2
  Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program
  ☆276Updated 7 years ago
• ritchie46 / vanilla-machine-learning
  vanilla machine learning
  ☆112Updated 2 years ago
• dimenwarper / awesome-bayes
  List of resources for bayesian inference
  ☆157Updated 6 years ago
• vinsis / understanding-neuralnetworks-pytorch
  Understanding nuts and bolts of neural networks with PyTorch
  ☆33Updated 4 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆240Updated 5 years ago
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆94Updated 2 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆191Updated 5 years ago
• gwgundersen / ml
  A didactic Python library with well-commented and annotated implementations of machine learning algorithms.
  ☆55Updated 4 years ago