The matrix calculus you need for deep learning


65 bookmarks. First posted by dlkinney july 2018.


Jeremy's courses show how to become a world-class deep learning practitioner with only a minimal level of scalar calculus, thanks to leveraging the automatic differentiation built in to modern deep learning libraries. But if you really want to really understand what's going on under the hood of these libraries, and grok academic papers discussing the latest advances in model training techniques, you'll need to understand certain bits of the field of matrix calculus.
calculus 
13 days ago by yizhexu
Jeremy's courses show how to become a world-class deep learning practitioner with only a minimal level of scalar calculus, thanks to leveraging the automatic differentiation built in to modern deep learning libraries. But if you really want to really understand what's going on under the hood of these libraries, and grok academic papers discussing the latest advances in model training techniques, you'll need to understand certain bits of the field of matrix calculus.
deeplearning  math  learning  howto  guides  machinelearning  neuralnetworks 
13 days ago by wesleythill
Jeremy's courses show how to become a world-class deep learning practitioner with only a minimal level of scalar calculus, thanks to leveraging the automatic differentiation built in to modern deep learning libraries. But if you really want to really understand what's going on under the hood of these libraries, and grok academic papers discussing the latest advances in model training techniques, you'll need to understand certain bits of the field of matrix calculus.
13 days ago by snafubar
Jeremy's courses show how to become a world-class deep learning practitioner with only a minimal level of scalar calculus, thanks to leveraging the automatic differentiation built in to modern deep learning libraries. But if you really want to really understand what's going on under the hood of these libraries, and grok academic papers discussing the latest advances in model training techniques, you'll need to understand certain bits of the field of matrix calculus.
14 days ago by vrt
> This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed. Note that you do not need to understand this material before you start learning to train and use deep learning in practice; rather, this material is for those who are already familiar with the basics of neural networks, and wish to deepen their understanding of the underlying math. Don't worry if you get stuck at some point along the way---just go back and reread the previous section, and try writing down and working through some examples. And if you're still stuck, we're happy to answer your questions in the Theory category at forums.fast.ai. Note: There is a reference section at the end of the paper summarizing all the key matrix calculus rules and terminology discussed here.

Co-written by Terrence Parr of ANTLR fame
15 days ago by briandk
The matrix calculus you need for deep learning The Matrix Calculus You Need For Deep Learning Brought to you by explained.ai (We teach in University of San…
from instapaper
16 days ago by rogerhsueh
Matrix Calculus for Deep Learning
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16 days ago by demon386
(We teach in University of San Francisco's MS in Data Science program and have other nefarious projects underway. You might know Terence as the creator of the ANTLR parser generator. For more material, see Jeremy's fast. via Pocket
IFTTT  Pocket 
august 2019 by domingogallardo
This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed.
maths  machinelearning 
july 2019 by sandipb
The Matrix Calculus You Need For
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AI  DeepLearning  BigData  from twitter_favs
june 2019 by cdrago
The Matrix Calculus You Need For
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AI  DeepLearning  BigData  from twitter_favs
june 2019 by TomRaftery
Brought to you by explained.ai (We teach in University of San Francisco's MS in Data Science program and have other nefarious projects underway. You might know…
from instapaper
march 2019 by matttrent
Reviews matrix derivatives. "This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed."
calculus  matrix-calculus  neural-networks  !M-⚽-methods-data-analysis-bayesian-statistics 
january 2019 by beyondseven
This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks
calculus  math 
january 2019 by force
(We teach in University of San Francisco's MS in Data Science program and have other nefarious projects underway. You might know Terence as the creator of the ANTLR parser generator. For more material, see Jeremy's fast.
IFTTT  Pocket 
december 2018 by timothyarnold
Jeremy's courses show how to become a world-class deep learning practitioner with only a minimal level of scalar calculus, thanks to leveraging the automatic differentiation built in to modern deep learning libraries. But if you really want to really understand what's going on under the hood of these libraries, and grok academic papers discussing the latest advances in model training techniques, you'll need to understand certain bits of the field of matrix calculus.
deeplearning  math  learning  howto  guides  machinelearning  neuralnetworks 
july 2018 by dlkinney