Alternatives and similar repositories for Matrix-Calculus-Tutorial

Users that are interested in Matrix-Calculus-Tutorial are comparing it to the libraries listed below

• ee227c / ee227c.github.io
  EE227C (Spring 2018) Course page
  ☆224Updated 4 years ago
• MLaPP-Solution-Manual / Solutions-to-Machine-Learning-A-Probabilistic-Perspective-
  Solutions to "Machine Learning: A Probabilistic Perspective"
  ☆162Updated 4 years ago
• joanbruna / MathsDL-spring18
  Topics course Mathematics of Deep Learning, NYU, Spring 18
  ☆544Updated 2 years ago
• percyliang / cs229t
  Statistical Learning Theory (CS229T) Lecture Notes
  ☆720Updated 5 years ago
• sailinglab / pgm-spring-2019
  Course webpage for PGM, Spring 2019.
  ☆76Updated 4 years ago
• deepgenerativemodels / notes
  Course notes
  ☆693Updated last year
• bamos / thesis
  Differentiable Optimization-Based Modeling for Machine Learning
  ☆338Updated 5 years ago
• PKUAI26 / Deep-Learning-Advanced-Topics
  ☆153Updated 5 years ago
• yousuketakada / prml_errata
  More PRML Errata
  ☆80Updated 2 years ago
• kushagra06 / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆121Updated 6 years ago
• t-vi / pytorch-tvmisc
  Totally Versatile Miscellanea for Pytorch
  ☆471Updated 3 years ago
• ws13685555932 / 18.065_lecture_notes
  lecture notes of "Matrix Methods in Data Analysis, Signal Processing, and Machine Learning"
  ☆150Updated 5 years ago
• ermongroup / cs228-notes
  Course notes for CS228: Probabilistic Graphical Models.
  ☆1,956Updated last year
• mlss-2019 / slides
  ☆260Updated 5 years ago
• mattjj / autodidact
  A pedagogical implementation of Autograd
  ☆984Updated 5 years ago
• mctorch / mctorch
  A manifold optimization library for deep learning
  ☆245Updated 3 years ago
• Atcold / SP19-DL-collaborative-notes
  Collaborative lecture notes for Spring '19 NYU DL class
  ☆119Updated 5 years ago
• YinTat / optimizationbook
  ☆140Updated last week
• tengyuma / cs229m_notes
  ☆229Updated 2 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 5 years ago
• google-deepmind / mc_gradients
  ☆168Updated 10 months ago
• rll / deepul
  ☆806Updated 2 months ago
• bob-carpenter / ad-handbook
  Automatic Differentiation Handbook
  ☆147Updated 4 years ago
• kilianFatras / awesome-optimal-transport
  A list of awesome papers and cool resources on optimal transport and its applications in general! As you will notice, this list is curren…
  ☆227Updated 4 years ago
• hjmshi / PyTorch-LBFGS
  A PyTorch implementation of L-BFGS.
  ☆602Updated 2 years ago
• soloice / Matrix_Derivatives
  This is a note on matrix derivatives and described my own experience in detail. Hope you'll like it.
  ☆559Updated 6 years ago
• davidbau / how-to-read-pytorch
  Quick, visual, principled introduction to pytorch code through five colab notebooks.
  ☆429Updated 5 months ago
• sangwoomo / ml-resources
  Personal and biased selection of ML resources
  ☆150Updated 5 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆277Updated 6 years ago
• ks838 / Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing
  Murphy's Machine Learning: A Probabilistic Perspective Errata (4th and later printings)
  ☆68Updated 5 years ago