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Record · corpus.blog/posts/01a07df3-adda-72d0-af01-dd7cf4db3d92

A Recipe for Training Neural Networks

Andrej Karpathy · published 25 April 2019

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Read the post at karpathy.github.io Wayback capture
19blogs citing
First cited
2 Sept 2018
Most recent
22 Jul 2026
Rank this month
not ranked
Links from this post
11
Words captured
3,987

Cited by

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4 Mar 2024
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30 Mar 2023
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4 Mar 2023
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How to initialize your bias. Read at the source ↗
24 Feb 2023
terencezl.github.io
Training Deep Learning Models Read at the source ↗
20 Dec 2022
blog.mariusvach.com
Kaggle RSNA Challenge 2022 Postmortem Read at the source ↗
13 Nov 2022
Windows on Theory
A blitz through classical statistical learning theory Read at the source ↗
31 Jan 2021
dsalaj.com
Corrupt, sparse, irregular and ugly: Deep learning on time series Read at the source ↗
20 Jun 2020
m-i-l
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14 Jun 2020
archy.deberker.com
Organizing applied machine learning research Read at the source ↗
12 May 2020
Twitch Blog
ThisEmoteDoesNotExist: Training a GAN for Twitch Emotes Read at the source ↗
24 Jul 2019
jeremyjordan.me
Organizing machine learning projects: project management guidelines. Read at the source ↗
2 Sept 2018
jeremyjordan.me
Organizing machine learning projects: project management guidelines. Read at the source ↗
2 Sept 2018
Max Halford
Links Read at the source ↗
—
thegustafson.com
Optimizers: Momentum, Adam, and Learning Rate Schedules Read at the source ↗
—

Links from this post

Link
Host
https://twitter.com/karpathy/status/1013244313327681536?lang=en
twitter.com
https://www.bigmarker.com/missinglink-ai/PyTorch-Code-to-Unpack-Andrej-Karpathy-s-6-Most-Common-NN-Mistakes
bigmarker.com
http://docs.python-requests.org/en/master/
docs.python-requests.org
https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b
medium.com
https://twitter.com/karpathy/status/801621764144971776?lang=en
twitter.com
https://openai.com/blog/learning-dexterity/
openai.com
http://vladlen.info/publications/playing-data-ground-truth-computer-games/
vladlen.info
https://arxiv.org/abs/1708.01642
arxiv.org
https://arxiv.org/abs/1801.05134
arxiv.org
http://jmlr.csail.mit.edu/papers/volume13/bergstra12a/bergstra12a.pdf
jmlr.csail.mit.edu
https://arxiv.org/abs/1503.02531
arxiv.org