Alternatives and similar repositories for Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing

Users that are interested in Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing are comparing it to the libraries listed below

• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆240Updated 5 years ago
• mlss-2019 / slides
  ☆260Updated 6 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆277Updated 6 years ago
• yousuketakada / prml_errata
  More PRML Errata
  ☆81Updated 3 years ago
• mlss-2019 / tutorials
  ☆275Updated 5 years ago
• MLaPP-Solution-Manual / Solutions-to-Machine-Learning-A-Probabilistic-Perspective-
  Solutions to "Machine Learning: A Probabilistic Perspective"
  ☆164Updated 4 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 6 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆92Updated 2 months ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 6 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆70Updated 7 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆109Updated 7 years ago
• ee227c / ee227c.github.io
  EE227C (Spring 2018) Course page
  ☆230Updated 4 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆122Updated 6 years ago
• stats385 / stats385.github.io
  STATS385 course website
  ☆89Updated 3 years ago
• xbresson / CE7454_2018
  Deep learning course CE7454, 2018
  ☆79Updated 6 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 7 years ago
• Atcold / SP19-DL-collaborative-notes
  Collaborative lecture notes for Spring '19 NYU DL class
  ☆118Updated 5 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 6 years ago
• Zhenye-Na / machine-learning-uiuc
  🖥️ CS446: Machine Learning in Spring 2018, University of Illinois at Urbana-Champaign
  ☆288Updated 6 years ago
• PhDP / mlbop
  Matlab code for S. Theodoridis' "Machine Learning: A Bayesian and Optimization Perspective" (2015).
  ☆71Updated 7 years ago
• odie2630463 / Restricted-Boltzmann-Machines-in-pytorch
  RBM in Pytorch
  ☆59Updated 8 years ago
• deeplearning-math / deeplearning-math.github.io
  A Course on Mathematical Theories of Deep Learning
  ☆79Updated 5 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆70Updated 7 years ago
• sangwoomo / ml-resources
  Personal and biased selection of ML resources
  ☆151Updated 5 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆76Updated 5 years ago
• zackchase / python-wow
  Python, so easy, wow!
  ☆140Updated 5 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆184Updated 7 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆326Updated 6 years ago