As a side note, one of the first machine learning programs I ever built was an email filter, which we called a "ham-spam classifier." Makes me almost want to get more emails! Almost.
If we made bagels average small as donuts J green bot will gets more lower precision , diameter and mass has no real causal relations to donuts and bagels. Learning depends on the real causal relations and procedure had been designed to experience. Also procedure design depends on real causal relations.
It's important to note that Supervised Learning and Neural Networks don't always have to go together. You can train a neural network using a different method, and you can use supervised learning on AI models other than neural networks.
Most of Algeria is in the Sahara desert although most of the population lives on the Mediterranean coast. I have a feeling that you already knew that though ;P معلومة تك
Guys I just want to say thankyou in name of HUMANITY! Your job is so important, and trust me im a communicator myself, I will spread this, and work for the utter common knowledge. Thanks, for real, THANKS.
Avec un nom comme Boudreau j'aimerais faire l'assomption que ton prof de science en primere était ton expérience avec Brain Pop, et vos etes alle à une école secondaire juste à l'autre bord de la rue lmao
I was wondering that too. I also love bagels. Sure, I don't want to bite into a bagel when I'm expecting a donut, and I don't want to bite into a donut when I'm expecting a bagel, but like... they're both good.
I disagree with the concept of toasting because I feel that it detracts from the texture and flavor of Noo Yawk bagels (and makes the cream cheese runny and messy). However, you've given me the idea of toasting donuts (particularly the "cake" type), in order to possibly achieve the consistency of home-baked corner pieces of cornbread!
A important mistake at 5:31 the electric action potential between neurons are all the same size,yes it is , but also real neuron has the different connection weights to other neurons, so real neuron can do the different size of signal too.
So I'm curious, is JohnGreen-Bot an actual AI computer? Or is it just hypothetical? I don't know much about computer science, but I really enjoy watching this course.
Well during human synapsis the comunication is not only electrical but electrochemical. The levels of that chemical components are what actually produce the answers or the neuron´s electrical shots and that levels are influenced also by many other environmental, genetical or individual inherent conditions. Then is not that easy compare humans and AI or create AI copying human behaviour.
@@TheTariqibnziyad Neuroscience it´s a multidisciplinary area. Then why an AI professional should be talking about biology concepts? It´s all about sharing knowledge, pal.
lol, I didn't catch the intro theme on the last video so I just thought John Green was tossing some voice clips at your for your channel... Here I am on the second video discovering this is Crash Course. Good on ya!
I did the initial lessons of the "artificial neural networks" course on Brilliant, which resemble this episode - and it was a light and helpful start. I would like to check the Coursera course too, ty :D
I know this is simplistic for the purpose of explaination but they really missed an opportunity to add a simple classification based on the ratio of mass to size. If it’s large it’s a bagel unless it’s light. Truly the fact that we’re picking light for donuts and heavy for bagels is good but Considering that all the data is there it makes more sense to do it as a ratio.
At 2:53 this description to neuron’s working mechanism is simple as too simple as easy to mistake students to understand. Reality the working mechanism of neuron has been designed more much complex than you think (because of natural selection). 3:10 neuron talking to each other by passing neurotransmitter (and the electrical signal is not the only way the neuron talking to another neuron) And the neuron isn’t using electric action potential directly to another neuron (this animation will makes you think wrong easy) the electric signal will makes the neurotransmitter transmit to another neuron and it will not save the energy if the previous one sends the neurotransmitter it doesn’t recognize.
And here's me, watching all of these, patiently waiting for some mention of bottom up AI. Both videos have been interesting so far, but mimicking human brain function to me is more realistic, if exponentially harder, for getting the results we're ultimately looking for.
Yeah, this has been an incredibly strange way to present it. I'm used to much simpler things like KNN or decision trees being taught early on instead of trying to jump straight into neural networks.
@@o76923 For example, I would consider an intelligent system, which uses hard-coded rules, generally an AI, but not ML unless it learns these rules by itself.
@@SaudBako, fair enough. I've just seen enough people refer to Intelligent Systems with hand coded rules as machine learning that I was willing to lump them together. If you do make a distinction between them, then you are correct.
Seriously, I'm worried about them not covering basics first. Is it assumed students came into this already having completed some other crash course series?
Why would you use mass and diameter to sort bagels and donuts? Wouldn't other characteristics like sweetness, appearance and providence be more useful? Eg. it looks like it has a frosted topping, it tastes sweet and it came from a donut shop, therefore it's a donut.
Fraser McFadyen He did mention that including more characteristics would increase the processing power needed. And the original objective is classifying it before tasting it.
of course it can , a standard audio cassette could hold around 130mb of audio data (like that of a dial up modem) thats plenty for simple AI. but cassette technology has come a long way. standard sized data cassettes used for backup and storage can hold MANY gigabytes of data, and some newer ones can hold more than a hundred terrabytes. ...the problem comes from random read cycles... it takes hours to load all of the data from the cassette.
This type of learning is slightly reminiscent of evolution by natural selection: if your "function for life" is fine, then you survive and all is well. If your "function for life" is not successful, then that particular combination of genes/programs dies out and can be replaced by a slightly different set of genes from another, perhaps more successful, individual. Not a perfect comparison but there is beauty in the system nonetheless.
Dude's so chilled that this crash course is actually in a normal pace.
That kid getting his test back at 1:47 is the most deeply relatable thing I've seen all day
My God that thumbnail is adorable. And the neurons. Whoever designs/animates these images is gifted.
It's the wonderful people over at Thought Cafe
I'm pretty sure they're the same neurons from Crash Course Anatomy, which btw is freaking awesome!
As an AI scientist, I appreciated everything in this episode, except for the ridiculous slander against bagels.
As a side note, one of the first machine learning programs I ever built was an email filter, which we called a "ham-spam classifier." Makes me almost want to get more emails! Almost.
Ikr? He is a bagelphobe.
I didn’t , not everything to learn from this RUclips
If we made bagels average small as donuts J green bot will gets more lower precision , diameter and mass has no real causal relations to donuts and bagels. Learning depends on the real causal relations and procedure had been designed to experience. Also procedure design depends on real causal relations.
Jabrils explains things using such a simple and understandable language. Love that guy
It's important to note that Supervised Learning and Neural Networks don't always have to go together. You can train a neural network using a different method, and you can use supervised learning on AI models other than neural networks.
This reminds me of Google having issues with nudity filters because the color and curves of sand dunes apparently are very similar to naked bodies 😂😂😂
Damn Algeria be looking extra thicc.
@@kekero540 Algeria ???!
Most of Algeria is in the Sahara desert although most of the population lives on the Mediterranean coast. I have a feeling that you already knew that though ;P
معلومة تك
So basically we will be replaced...
*fertilize the desert*
2:53 I had no idea neurons were this cute
@Karan it's plural
I was so surprised to see my favorite youtuber hosting my favorite youtube series
Awesome, I love that this course is now available!
10% comments: about AI itself,step function
90% comments: Why he hate bagels?
Sadly not even 10%
I wonder how many understand that he was just memeing. Digging at John Green's love for bagels as an homage to prior CrashCourse series.
@@Ryan-wk3mc We do now
The commitment is real, holding up 48 different donuts or bagels so a 'robot' can pretend to determine the outcome
+
I wonder who ate all these 100+ donuts and bagels after filming
John Green: relaxing
Also John Green: see 75 begels
John Greenbot.
Edit: Imagine some guy walking in the their local bakery like: "Hey Jim, I need 100+ assorted bagels... It's for a video."
11:14 slow down to 0.25x you will see he was not pushing the button
love his outgoing and chilled personality. But he talked about doughnout so much that I'm craving one right now. Lol!
Its so good to see a someone explaning something i learned in college, but this animations
Super helpful! Cleared up what bias meant in this context. Thank you!
Guys I just want to say thankyou in name of HUMANITY! Your job is so important, and trust me im a communicator myself, I will spread this, and work for the utter common knowledge. Thanks, for real, THANKS.
I absoutely love this series. Honestly so amazing.
This guy is the modern day Tim and moby from brain pop
Avec un nom comme Boudreau j'aimerais faire l'assomption que ton prof de science en primere était ton expérience avec Brain Pop, et vos etes alle à une école secondaire juste à l'autre bord de la rue
lmao
Awww yeah!!
Hey, what's all this hate on bagels about? I love bagels!
I was wondering that too. I also love bagels. Sure, I don't want to bite into a bagel when I'm expecting a donut, and I don't want to bite into a donut when I'm expecting a bagel, but like... they're both good.
Hope?
Toasted bagels with cream cheese are great!
you are making me hungry! I'm going for a bagel now...
I disagree with the concept of toasting because I feel that it detracts from the texture and flavor of Noo Yawk bagels (and makes the cream cheese runny and messy). However, you've given me the idea of toasting donuts (particularly the "cake" type), in order to possibly achieve the consistency of home-baked corner pieces of cornbread!
Best explanation of precision and recall that I've seen!
I love the pacing of this Crash Course. And I will go buy a donut now
Thank your perfect explanation for AI love ❤️ your RUclips, this is the highest quality series teach AI on RUclips
This episode reminds me of when I had to make KNN models in R.
This is a great series btw, very helpful in understanding AI. Thanks
Sweet bagels are basically donuts. No one tell poor greenbot
I am So ready for this Course
Learning is the key!
I’m kinda jealous how this guy has donuts and bagels, makes me hungry
9:46 “learns from failure, but not from success” Just like humans
Damn! He electrocuted the perceptron when it got the answers wrong
John Greenbot got a B- on the bagel vs donut test. That's good enough for school!
Woah he talking and not just dubbing over his voice, this is weird
Who the heck buys 75 bagels and only 25 donuts.
A monster.
Great, helpful video. Your videos never fail to impress me 🙏
who else thinks that his voice is do soothing and he should make a podcast??
Nice to see R.O.B take a break from Smash Bros to join CrashCourse.
This series is amazing and so well made!
love the video, I learned that donut is better than bagels thankyou
The meanest and probably the most elaborate AI algorithm of all is the one putting you in the friend zone
A important mistake at 5:31 the electric action potential between neurons are all the same size,yes it is , but also real neuron has the different connection weights to other neurons, so real neuron can do the different size of signal too.
This single video helped me understand 10x more of what i understood in my lecture. Thank you
Crossing the Bagel Threshold was the name of my band at fat camp.
I love the cassette tape!
This learning mechanism is one way to design a procedure If Define Design as to select the iteration changing with more successful of adapting goal .
So I'm curious, is JohnGreen-Bot an actual AI computer? Or is it just hypothetical? I don't know much about computer science, but I really enjoy watching this course.
You gotta teach John Greenbot how to keep his bagel from getting away!
By putting lox on it!
+
It’d be really nice if you also touched the XOR problem.
Jabril is the world most advanced artifical intelligence :)
Well during human synapsis the comunication is not only electrical but electrochemical. The levels of that chemical components are what actually produce the answers or the neuron´s electrical shots and that levels are influenced also by many other environmental, genetical or individual inherent conditions. Then is not that easy compare humans and AI or create AI copying human behaviour.
Go to crash course biology, this is not your place pal.
@@TheTariqibnziyad Neuroscience it´s a multidisciplinary area. Then why an AI professional should be talking about biology concepts? It´s all about sharing knowledge, pal.
Nice job getting Omnibot 2000!
lol, I didn't catch the intro theme on the last video so I just thought John Green was tossing some voice clips at your for your channel... Here I am on the second video discovering this is Crash Course.
Good on ya!
I can't wait until this course translated to Arabic to fully understand this exciting course !!
Please hurry up 🙃 😥
3:45 Cornell represent!
I made the Machine Learning course at Coursera, it was nice.
I did the initial lessons of the "artificial neural networks" course on Brilliant, which resemble this episode - and it was a light and helpful start. I would like to check the Coursera course too, ty :D
Bagels>donuts... For a super smart guy he's got some underdeveloped taste buds...
Awesome course. Nice job! I am enjoying it 😍
Everything is delicious, unless of course, they are the bagels. **Insert Bagel Montage**
I love bagels and my nickname at school is bagel
Bagels are good too.
I know this is simplistic for the purpose of explaination but they really missed an opportunity to add a simple classification based on the ratio of mass to size. If it’s large it’s a bagel unless it’s light. Truly the fact that we’re picking light for donuts and heavy for bagels is good but Considering that all the data is there it makes more sense to do it as a ratio.
jabril : blah blah blah
john green bot : HELLO HUMANOID FRIEND
I think it's super funny that John Green-bot's programs are saved on cassettes! LOL
Nice video..!!
green bot's voice is quite similar to "Sheldon cooper" voice from Big Bang theory
I like a good dounut but Bagles are my go to day to day.
At 2:53 this description to neuron’s working mechanism is simple as too simple as easy to mistake students to understand. Reality the working mechanism of neuron has been designed more much complex than you think (because of natural selection).
3:10 neuron talking to each other by passing neurotransmitter (and the electrical signal is not the only way the neuron talking to another neuron)
And the neuron isn’t using electric action potential directly to another neuron (this animation will makes you think wrong easy) the electric signal will makes the neurotransmitter transmit to another neuron and it will not save the energy if the previous one sends the neurotransmitter it doesn’t recognize.
Thank you for this information!
I like John Green Bot.
Madlad actually counted 100 donuts/bagels
Thanks John Green Bot!
Bot: Bagel!
Cool decor
What's up w jabril being against bagels?? They're so good, especially with cream cheese!
yall are really smart
Very good!
I never ate a doughnut before, and what is a bagel?
We haven’t master how to have friendly conversations yet. 😆
And here's me, watching all of these, patiently waiting for some mention of bottom up AI. Both videos have been interesting so far, but mimicking human brain function to me is more realistic, if exponentially harder, for getting the results we're ultimately looking for.
Yeah, this has been an incredibly strange way to present it. I'm used to much simpler things like KNN or decision trees being taught early on instead of trying to jump straight into neural networks.
Amazing that ai code can fit on a cassette tape
"I don't wanna bite into a donut and it turns out it's a bagel.", better than biting into a choc chip cookie and finding out they're raisins.
Not all AI needs to learn. All ML systems need to learn, but not all AI.
Not all machine learning systems learn either, counter-intuitively. Some are just algorithms that don't have a learning process.
James Endicott I thought Machine LEARNING means that the computer is learning. What kind of ML "algorithm" doesn't learn?
@@o76923 For example, I would consider an intelligent system, which uses hard-coded rules, generally an AI, but not ML unless it learns these rules by itself.
@@SaudBako, fair enough. I've just seen enough people refer to Intelligent Systems with hand coded rules as machine learning that I was willing to lump them together. If you do make a distinction between them, then you are correct.
I am kinda lost on how the random weighing of Greenbot works
Also this is a wonderful course
What do you mean by "In our brains, the electric signals between neurons are all the same size"?
Very nice.. Thanks!
This episode gives the impression that supervised learning is neural networks and neural networks only. That makes me sad.
Seriously, I'm worried about them not covering basics first. Is it assumed students came into this already having completed some other crash course series?
Why would you use mass and diameter to sort bagels and donuts? Wouldn't other characteristics like sweetness, appearance and providence be more useful? Eg. it looks like it has a frosted topping, it tastes sweet and it came from a donut shop, therefore it's a donut.
Fraser McFadyen
He did mention that including more characteristics would increase the processing power needed.
And the original objective is classifying it before tasting it.
Dude, I don't know the difference between Bagels and Donuts, and it's not a big deal!
I really really want a donut now.
9:48 😆😂😂😂From Failure not from success
I love bagels
I dislike this man's disgust in bagels
*BAGELS ARE AWESOME*
This remind me of school.
Why do you hate bagels?
Some people just don't like some foods.
Personal preference
I did not know that an AI program could fit on an old cassette tape.
of course it can , a standard audio cassette could hold around 130mb of audio data (like that of a dial up modem) thats plenty for simple AI.
but cassette technology has come a long way. standard sized data cassettes used for backup and storage can hold MANY gigabytes of data, and some newer ones can hold more than a hundred terrabytes. ...the problem comes from random read cycles... it takes hours to load all of the data from the cassette.
@@Great.Milenko Oh, what fun 😃
What are the blinking lights behind him doing? It looks like it might be the game of life, sorta.
This type of learning is slightly reminiscent of evolution by natural selection: if your "function for life" is fine, then you survive and all is well. If your "function for life" is not successful, then that particular combination of genes/programs dies out and can be replaced by a slightly different set of genes from another, perhaps more successful, individual. Not a perfect comparison but there is beauty in the system nonetheless.
Cool!
Awesome!
I like this