It has been customary for the users of different communities to quote funny things about their fields. It may be fun to share your funny things about Machine Learning, Deep Learning, Data Science and the things that you face every day!
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1$\begingroup$ Not quite data science, as it's more data management & archiving, but see youtube.com/watch?v=N2zK3sAtr-4 $\endgroup$– JoeDec 15, 2018 at 23:36
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4$\begingroup$ I like this, but really, does this belong here? Maybe it's better off on the Meta. $\endgroup$– Mr ListerDec 16, 2018 at 14:55
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2$\begingroup$ related: stats.stackexchange.com/questions/1337/statistics-jokes and stats.stackexchange.com/questions/423/… $\endgroup$– moooeeeepDec 17, 2018 at 7:30
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2$\begingroup$ How many epochs will we need to find ourselves in an epoch (Hellenic meaning), where the machine learning algorithm can make good jokes, to post here? $\endgroup$– gsamarasDec 18, 2018 at 10:45
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2$\begingroup$ @jkf the moderators have the ability, power, strength, force, capability, right and intention to make the short answers to comments. They are powerful creatures. You also can track the boxing match. $\endgroup$– Green FalconDec 19, 2018 at 8:36
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13 Answers
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Q: How many machine learning specialists does it take to change a light bulb?
A: Just one, but they require a million light bulbs to train properly.
Q: How many machine learning specialists does it take to change a fluorescent light bulb?
A: That wasn't in the training data!
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5$\begingroup$ I usually find light bulb jokes boring, but this one is cool :D $\endgroup$ Dec 14, 2018 at 15:38
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3$\begingroup$ @JérémyBlain All the other light bulb jokes were training - we now have to rerun them with this as a model. $\endgroup$ Dec 18, 2018 at 14:19
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1$\begingroup$ Ah, yes, there is xkcd about everything! $\endgroup$ Dec 14, 2018 at 20:47
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If you torture data long enough, it will tell you whatever you want to hear.
Statistics shows that statistics cannot be trusted.
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I find this funny because it's true.
Cute funny...
This one always cracks me up for no reason...
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1$\begingroup$ But but but, the bar with the large uncertainty is the only one I trust. Who would trust someone who claims to be absolutely sure of everything, rather than the one who rightly puts in a realistic level of uncertainty? $\endgroup$– gerritDec 16, 2018 at 12:41
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Question: What's the different between machine learning and AI?
Answer:
If it's written in Python, then it's probably machine learning.
If it's written in PowerPoint, then it's probably AI.
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Frequentists vs. Bayesians
Transcript:
Did the sun just explode?
(It's night, so we're not sure)[[Two statisticians stand alongside an adorable little computer that is suspiciously similar to K-9 that speaks in Westminster typeface]]
Frequentist Statistician: This neutrino detector measures whether the sun has gone nova.
Bayesian Statistician: Then, it rolls two dice. If they both come up as six, it lies to us. Otherwise, it tells the truth.
FS: Let's try. [[to the detector]] Detector! Has the sun gone nova?
Detector: <<roll>> YES.Frequentist Statistician:
FS: The probability of this result happening by chance is $\frac1{36}=0.027$. Since $p< 0.05$, I conclude that the sun has exploded.Bayesian Statistician:
BS: Bet you $50 it hasn't.
Title text:
'Detector! What would the Bayesian statistician say if I asked him whether the–' [roll] 'I AM A NEUTRINO DETECTOR, NOT A LABYRINTH GUARD. SERIOUSLY, DID YOUR BRAIN FALL OUT?' [roll] '... yes.'
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Let me embrace thee, sour adversity, for wise men say it is the wisest course.
Yann Le Trump! 😂😂😂
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Unsure whether they qualify, but there are some fun facts taken from various sources:
Beginning from Yann Lecun:
Geoff Hinton doesn't need to make hidden units. They hide by themselves when he approaches.
Geoff Hinton doesn't disagree with you, he contrastively diverges
(from Vincent Vanhoucke)Shakespeare and Bayes are in a boat, fishing. Bayes is trying to figure out which net to cast when Shakespeare says: "loopy or not loopy? that is the question".
Deep Belief Nets actually believe deeply in Geoff Hinton.
Geoff Hinton discovered how the brain really works. Once a year for
the last 25 years.Bayesians are the only people who can feel marginalized after being integrated
And now the legend:
One from Reddit:
YOLO: you only LEARN once
P.S: Ian Goodfellow and Jurgen Schmidhuber are co-authoring a paper (to be presented at NIPS 2019) on Inverse GANs (More jokes on the topic here)
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A Machine Learning algorithm walks into a bar.
The bartender asks, "What'll you have?"
The algorithm says, "What's everyone else having?"
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"Predictions are hard -- especially about the future."
(Yogi Berra or Neils Bohr, depending whether you prefer physics or baseball)
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A: What is machine learning sir? B: It is not machine learning! It is machine burning, man.
by Davide Mazzini
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In 2006, a common joke was that you would get an award for writing a paper that would either have "Karl Marx" or "Neural Network" in the title and get accepted at NIPS. Now that's become the standard for the latter... :D