Machine Learning is not just a buzzword; it’s the high-tech wizardry that’s granting our computers the uncanny ability to think, predict, and sometimes even act a smidge rebellious. Picture this: instead of tediously coding software to execute specific tasks, we feed our devices heaps of data, like overenthusiastic parents with a spoon of mashed peas, and voila, they magically learn from the data and get better over time. It’s like training your pet, only these pets can recognize your face, recommend you movies, or, in more sinister scenarios, finally realize you’re terrible at keeping indoor plants alive.
Now, why do Machine Learning jokes tickle our funny bones? Simply put, we’re all a tad wary of our gadgetry getting too smart. It’s one thing for your phone to suggest a restaurant, but quite another if it starts critiquing your dating choices! Thus, the internet is filled with hilarious anecdotes like, “Why did the Machine Learning model break up with the gradient? Because it was feeling stuck in a local minimum!” These puns are a mix of genuine geeky humor and our collective way of coping with the eerie idea of a coffee machine one day refusing our brew request due to our caffeine intake. Embrace the laughs, because if machines start cracking jokes better than us, we’re truly in uncharted waters!
Best Machine Learning Jokes
Did you hear about the programmer who developed a VS Code extension that uses machine learning to tell you when you’ve made an obvious mistake?
It’s called ObVS.
How does a very bad machine learning model greet its friends?
“Hi, bias! Hi, variance!”
Why are compilers so bad at optimizing poker algorithms?
Because of their constant folding!
Yo mama’s like an outdated algorithm, even machine learning can’t improve her performance.
What do you call a machine learning Ph.D. candidate student who’s academic work is getting worse and worse?
Grad on Descent.
What are quants who employ deep learning techniques called?
Quants with GANs.
Knock, knock.
(Who’s there?)
Tensor.
(Tensor who?)
Tensor you’ve been waiting for to complete that neural network!
What do you say when a scientific computing job crashes after running for weeks on the cluster?
That’s very unFortranate.
Did you hear about the programmer who invented an efficient signal-processing algorithm to calculate changes between two files of Japanese text?
Fast and Fouriers: Tokyo Diff.
What do you call a neural network of which the output is a uniform distribution?
A neutral network.
What do you call a difficult question in multilinear algebra?
A brain tensor.
A machine learning algorithm walks into a bar.
The bartender asks, “What would you like to drink?”
The algorithm replies, “What’s everyone else having?”
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Which deep learning algorithm is used to try to control plasma reactors?
Stable-the-fusion.
What do you call a model longer than 350 lines?
A size plus model.
Why did the naive Bayesian suddenly feel patriotic when he heard fireworks?
He assumed independence.
Why are linear time algorithms preferred?
They always run O(n) time.
Interviewer: What’s your biggest strength?
Interviewee: I’m good at Machine Learning
Interviewer: Okay, what’s 21+17
Interviewee: It’s 5
Interviewer: Not even close. It’s 38
Interviewee: It’s 20
Interviewer: I said it’s 38
Interviewee: It’s 35
Interviewer: It’s still 38….
Interviewee: It’s 38
Interviewer: Hired!
Which part of a program likes cocaine?
The snorting algorithm.
What do you say when someone publishes a new quantum algorithm for breaking encryption?
Without a working quantum computer, it’s just for Shor.
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Why did the drug-addict find that he really likes programming?
He liked the hash tables.
A company develops a machine for evaluating IQ.
The scientists developing it ask for the help of the supervisor, manager, and president of the firm to test the machine.
When the supervisor placed his head on the machine, it responded: ‘IQ 160’, and he was very impressed.
When the manager placed his head on the machine, it responded: ‘IQ 170’, and he was very impressed.
When the president placed his head on the machine, it hummed for a bit and responded, “This is a very sensitive machine, please do not use rocks as test subjects’, and the president was furious.
After hurried improvement, the scientists asked the three to try again. This time the machine gave the manager an IQ of 165, and the supervisor an IQ of 170 and both were very happy, saying it was more accurate.
After the president placed his head on the machine, it hummed for a bit and responded: ‘This is a very hot rock’, and the president was furious, threatening to fire the scientists.
After a third improvement phase, the scientists assured everyone that the machine was perfect. This time, the supervisor was given an IQ of 170, and the supervisor an IQ of 175. Both praised the machine stating that it was perfect and urged the president to try again.
Having learned from his past mistakes, this time the president decides to place the rock onto the machine first. After some humming, the machine responded, “Welcome Mr president!”
A Machine Learning algorithm walks into a bar.
200 times.
What is the smallest member of the Secure Hash Algorithm family?
Baby SHA doo doo doodoo doodoo.
How does a programmer prepare corned beef?
Using a hash method.
Why did the machine learning model bring a ladder to class?
To reach the higher layers!
A customer walks into a Generative Adversarial Bar. He approaches the bartender and says “I’ve been to every other bar in this city and sampled everything they have to offer. Give me a beer.”
The bartender, being new to the job, responds by smashing a glass on the counter and spraying it with beer from the tap. “How’s that?”
“That’s not how they serve it next door,” says the customer. “I’ll keep that in mind”, replies the bartender.
What do a Machine Learning specialist and a Fashion Designer have in common?
They both specialize in curve-fitting.
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What algorithm does Amber Heard use to dig for gold?
Depp First Search.
How do you comfort a sad machine learning model?
“There, there, it’s just a phase. You’ll converge soon.”
Two pirates have just finished developing a machine with the ability to think and learn.
The first pirate says, “This is amazing! You should come up with a name for this.”
The second pirate says, “AI, captain!”
What are bakers’ favourite algorithm?
Bread First Search.
How do you make an algorithm more flavorful?
Add a Boolean cube.
Why did the deep learning model break up with the gradient?
It had too many descent issues!
Did you hear that the neural network went to the gym?
It wanted to work on its backpropagation.
Why did the machine learning model get kicked out of school?
It had too many layers!
The physicist could not get any job, so he decided to bet on horse races to make a living.
He did intensive experimentation and used state-of-the-art machine learning algorithms to gain more insight. After filling many notebooks and accumulating a very large amount of data, he exclaims, “I have the solution, but it works only in the case of spherical horses of uniform density applying a uniform force in a closed system and a vacuum.”
After over 500 iterations a machine learning algorithm crab walks into the bar instead of the wall. The bartender asks “What’ll you have”, the algorithm crotch thrusts into the air.
There are 10 types of people in the world.
Those that understand binary.
Those that don’t.
And the weirdos counting in base3.
How do astronomers simulate Cepheid star clusters?
With lots of glow-ball variables.
If all your friends jumped off a bridge would you follow them?
Machine Learning algorithm: yes.
Why did the machine learning model go to therapy?
It had too many biases!
What did the machine learning algorithm say to the dataset?
“I can’t make you happy, but I can minimize your errors!”
Why did the computer call its parents?
To let them know it found its perfect match on a dating website—they were a great “data” set!
How does a machine learning model apologize?
“Sorry, I can’t classify your feelings right now.”
Do you have a funny Machine Learning joke? Write down your own ML puns in the comment section below!
They say we should be wary of machines that can learn and think…
How quickly they forget that artificial intelligence is not real smart.