dear sweet baby jesus. You just gave my brain a breakthrough, this is probably the best introductory course on Neural Nets on the internet. Thank you Luis!
00:00 What is machine learning ? 2:22 Gradient descent 5:07 Neural network 10:11 logistic regression 12:28 Probability 14:57 Activation Function 19:56 Error function 22:34 Node(Neuron) 24:07 None liner regions 31:22 Deep neural network
why did I not find this video before!!! this is amazing, Luis. You are clearly a very talented teacher, thank you so much. Omg those Stanford and MIT lectures are making so much more sense.
I am at the loss of words to describe how helpful it was to understand the basics of neural networks. For me, neural networks are not scary anymore. Thank You!
I am sorry, but I can not stop myself to praise Luis. He has gene of explain complex things. I recommend his videos to all new learners. Nobody able to explain such clear.
Here in 2024 and been trying to wrap my brain around this stuff for a couple years. Your vids have absolutely made it all click. Well done and many thanks!
Looked sooo many "wannabe easy" videos on this stuff which all skip essential parts like I learned now - I come to think that they don't even understand it at such a level as you did... - now i finally understand it! Please continue your videos!!!!
You have explained so many foundational insights and distilled multiple concepts in deep learning and artificial neural networks all in one video of just around half an hour. You are amazing. I feel like have a unique perspective on deep learning now and can grasp higher concepts. Thank you Luis.
i am from bangladesh i was search for neural networks easy expalined video......few days. i found your video. and its realy best explanation video......first 2 example is best to explained about neural networks
Deat Mr Serrano, I am a electrical engineer student in germany who tries to get more knowledge on the field of artifical intelligence and its sub - and subsubtopics machine learning and deep learning. This video gave me pretty good imagination of the mathematical formulars behind all the magic and that's why I want to thank you, thank you !
I'm just going to reiterate what I've already said in other comments: your talent to turn very complex subjects into visual representations and easy words is truly inspirational. If Unis had more people like you there would be scientists and this would be a better world. Can you please story-tell us around Feature Engineering?
Thank you Alessia! Yes, I'm definitely due to make a feature engineering one, hopefully soon! In the meantime, this video touches on it: ua-cam.com/video/aDW44NPhNw0/v-deo.html
These intro courses on you channel, are too good. Before some months, I started ML, without learning these basics, this was harder to jump on mathematics behind ML. Now, I know how and why those formulas were applied in ML problems.
You nailed it.. Having talent is important but need a lot of intelligence to explain it. You really made my life easy.. Awesome...please go ahead and teach as much as you can...we are thankful to you sir..
how well a person can explain complicated things to be easily understood shows the level of cognitive intelligence he possesses. Did i mention Luis you are one of those people ?
I reserved my first comment on UA-cam for something like this. I second my thoughts with Joao Sauer. This a testimony to how human mind is still the most intelligent computer that could help translate a complicated subject to a simple model. Thanks Luis Serrano. This is very helpful. Appreciate your effort in putting this together.
Dear Luis, great work. There are no words that can be described by any neural network to than what you have been doing and keep it up. May God bless you with everything you need in life.
Maybe Im missing the simplest point of it all, at 20:37 how do we get the log values ? E.g. how does -log(0.1) become 2.3 (instead of 1?) and how do we get the 4.8 as a sum? What am I missing? :) EDIT: I just realised it's a natural log (so ln(0.1) = 2.3 instead of log10)...I'll leave this up here in case someone else missed it as I did instead of deleting the question. Otherwise the best explanation on the topic ever! Thanks!
What a great entrance for a complete newbie to the the topic!! Especially the beginning with the cake helped so much with actually getting behind the idea before understanding HOW it actually works. Many others missed that point completely ....
Superb presentation, most people will be wondering what hidden layers are and what part they play, this clears it up of course the next question is how does one choose x or y hidden layers
Thanks for this excellent explanation. One question: at 17:15 what are you measuring? is it blueness? According to the probability function, shouldn't the most left-top point be scored with something close to 1.0? Why the 0.1? Points close to the top left corner are believed to be "most likely" blue, right?
That was brilliant! Thank you so much. As a statistician I understand all the bits that go into making the neural network, your explanation was the most intuitive I have ever seen of how they all come together to make a neural network. You know those moments where you have spent ages trying to figure something out then something just clicks, and you say! "Ahhh, is that it? It is so simple". Well, your video just gave me one of those moments. I wish I could give you more than one like.
this was THE BEST lecture that has explained neural networks. thank u!! Very Clear Explanation! I feel comfortable moving forward with this topic! Well done ✔ Thanks best regards from Egypt 😍
Great video. Thanks so much. This is the best explanation of neural networks I ever watched. Conceptually speaking is the “filter” of a convolutions neural network analogous to the hidden layers.
Jabril recommended this to me. I first went to giant’s neural network series and learned the bare basics. Then naturally the question came to my mind, why would we need multiple (hidden) layers of neurons. This video just blew that doubt to smithereens. Thank You!
Thank you for the opportunity to gain some understanding of a subject which looks to be completely outside a completely unrelated profession but may be something that fascinates a few of us in terms of what potential it may hold if we think outside of the box. Thank you for your time and effort.
Thank you Rhonda! I find this fascinating too, and machine learning is definitely a field that many professions can use, so I think it should be accessible to people with all types of backgrounds, not only math/cs.
This is so good, it illustrates clearly now an n-dimensional arbitrary shape in the data can be defined by the lines specified by neuron pairs. That shape specifies something the enclosed/defined data have in common. I loved it.
Thank you so much for posting this video and help me a lot. When i was student, the instructor focus on backpropagation derivation and i never fully understand the concept of neural networks. Thank You Again!!
Thank you for your message, Safa, it is an honor to hear that. Best of luck in your learning process, and if you have any questions or suggestions, let me know! :)
It is really friendly as per the title. The examples used are very appropriate and excellent. The explanation is fantastic, anyone with the interest of learning can understand. Using these simple examples I can easily make my students understand the concept of machine learning. Thanks for your good service.
Wow, seriously Wow... this video should be shown to every individual who is interested to know and learn Neural networks. unlike most of the lectures which tend to drive the AI & ML students away with complex explanations , this video brings them closer to this subject with simplifying the explanations. i am amazed at the topics covered in this video like 1: Why do we need to convert from discrete to continuous 2: what's the need of an error function 3: why neural networks are even needed and what are they 4: what are activation functions and how to make sense of it 5: hidden layers explanation 6: optimization, minimization, whats the whole point of summing the errors etc etc etc Awesome video which i am gonna share with every AI ML enthusiast. thanks for the wonderful video @luis Serrano
I really had a hard time grasping the basic concepts of the neural network by reading a couple of tutorial and articles on this topic. But this video just blew my mind. It is simply the best. Thanks a lot @luis for this awesome explanation.
This was so unbelievably awesome thank you. I've been struggling to understand this stuff for months and your video made it completely obvious. Thank you!!
On a second thought, it would be great if you could come up with an example (like ML Intro video) showing NN in use. Maybe you can include concepts for WEIGHTS, FEEDBACK LOOP, TERMINATION CRITERIA and so on. Once again many thanks for creating the video. Really appreciate all your efforts!
Thank you for the suggestion, Nilesh! Yes, working on a few more videos, including one where the training part is explained in more detail. Feel free to send any other suggestions you may have, always open to new ideas!
This video helped me understand what a neural network is! Thanks for explaining it in such an easy to understand way. I would recommend it to all beginners.
Luis, very well explained. I have seen many articles and video on ML and NN. Your video provides a "deep" understanding of the basics of Neural Networks and provides insights in solving problems with them. Thank you.
Thanks for turning a research matter into a cartoon-like story wherein anyone's curiosity is developed and is forced to see each of your well dedicated videos. Hats off to your determination to help the research community.
Thank you for your kind words Sandeep! I enjoy understanding things in a pictorial way, and I'm glad that more people in the research community also feel this way.
Yes man. Great job teaching. I also enjoy when you share your mind through metaphors, for example, the line in the sand, and the magnifying glass. Thank you for making the video.
I like the way it is presented this complicated topic. Very effective method of simplifying the cryptic topics. Please do post such videos. Really appreciate it.
Thanks for making this video, by not using typically well known images of neural networks, it prevented a lot of mental blocks when watching other videos 🤗🤗🤗
I can only echo the other comments; what an outstanding introduction to an often obscurely taught area!!! Thank you so much, Luis! Keep up the good work.
![Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]](/img/n.gif)
dear sweet baby jesus. You just gave my brain a breakthrough, this is probably the best introductory course on Neural Nets on the internet. Thank you Luis!
you are Jabrils..wow..It's like one Ninja ML master hosting another Ninja ML Master.Historic moments..
Oh you 2 gentlemen, great videos
you 2 help me develop. thank you
00:00 What is machine learning ?
2:22 Gradient descent
5:07 Neural network
10:11 logistic regression
12:28 Probability
14:57 Activation Function
19:56 Error function
22:34 Node(Neuron)
24:07 None liner regions
31:22 Deep neural network
This is BY FAR the best explanation of ANY topic that I've ever seen. A true talent. Thank you so much for this!
Finally i found (math) teacher who taught me how i wanted to be taught with examples in maths Gradient descent was ❤️
why did I not find this video before!!! this is amazing, Luis. You are clearly a very talented teacher, thank you so much. Omg those Stanford and MIT lectures are making so much more sense.
I am at the loss of words to describe how helpful it was to understand the basics of neural networks. For me, neural networks are not scary anymore. Thank You!
You must be the best AI, ML, DL teacher I've ever watched on UA-cam - I watched A LOT of them.
I am sorry, but I can not stop myself to praise Luis. He has gene of explain complex things. I recommend his videos to all new learners. Nobody able to explain such clear.
I believe one can only teach subject if he/she understand the subject and this is what Luis proved. Very simple and crisp clear explanation.
One thing is for sure: You can't teach X well if you don't know X well. I agree with you
"But then I saw a real neural network and realized it was much scarier than that."
Okay, bonus points
Here in 2024 and been trying to wrap my brain around this stuff for a couple years. Your vids have absolutely made it all click. Well done and many thanks!
This is the best "what are neural networks" video i have ever watched. Amazing !! Thanks a lot ❤️.
Looked sooo many "wannabe easy" videos on this stuff which all skip essential parts like I learned now - I come to think that they don't even understand it at such a level as you did... - now i finally understand it! Please continue your videos!!!!
Gracias Luis. Very helpful for a 65 years old beginner like me.
This lit up some neural pathways in my brain. Thank you for explaining with so much clarity and sharing knowledge with us.
Luis serrano...you are the best teacher. Bestest explanation i have ever seen. Thank you so much for the video.
You have explained so many foundational insights and distilled multiple concepts in deep learning and artificial neural networks all in one video of just around half an hour. You are amazing. I feel like have a unique perspective on deep learning now and can grasp higher concepts. Thank you Luis.
This is the best ML video in explaining what hidden layers do versus taking them as blackboxes. Thank you!
i am from bangladesh
i was search for neural networks easy expalined video......few days.
i found your video.
and its realy best explanation video......first 2 example is best to explained about neural networks
Deat Mr Serrano,
I am a electrical engineer student in germany who tries to get more knowledge on the field of artifical intelligence and its sub - and subsubtopics machine learning and deep learning. This video gave me pretty good imagination of the mathematical formulars behind all the magic and that's why I want to thank you, thank you !
Sir you are one of the most genus sir in this world .you made me understand this lessons that i could not understand .thank a bunch
Most friendliest explanation of neural networks I have seen in youtube, so far.
Again, Luis has such an amazing ability to explain concepts clearly
I'm just going to reiterate what I've already said in other comments: your talent to turn very complex subjects into visual representations and easy words is truly inspirational. If Unis had more people like you there would be scientists and this would be a better world. Can you please story-tell us around Feature Engineering?
Thank you Alessia! Yes, I'm definitely due to make a feature engineering one, hopefully soon! In the meantime, this video touches on it: ua-cam.com/video/aDW44NPhNw0/v-deo.html
@@SerranoAcademy Watched it yesterday, Loved how you explained underfitting and overfitting with Godzilla and a Bazuca! :))
Just want to leave a comment so that more people could learn from your amazing videos! Many thanks for the wonderful and fun creation!!!
These intro courses on you channel, are too good. Before some months, I started ML, without learning these basics, this was harder to jump on mathematics behind ML. Now, I know how and why those formulas were applied in ML problems.
You nailed it.. Having talent is important but need a lot of intelligence to explain it. You really made my life easy.. Awesome...please go ahead and teach as much as you can...we are thankful to you sir..
how well a person can explain complicated things to be easily understood shows the level of cognitive intelligence he possesses.
Did i mention Luis you are one of those people ?
You are really gifted at breaking down complex concepts into an easily understood analogy. That is a gift not many have. Keep up the amazing work!
seriously. it ws the best video ever explaining neural networks with visualization in such simplified way.
I reserved my first comment on UA-cam for something like this. I second my thoughts with Joao Sauer. This a testimony to how human mind is still the most intelligent computer that could help translate a complicated subject to a simple model. Thanks Luis Serrano. This is very helpful. Appreciate your effort in putting this together.
Beautiful explanation brother! 7 years later and still one of the best explanations
This is so much more clear than all of tho other videos on this topic, than you.
Really awesome presentation !! Clearly describes the core methodology of Neural Networks
Thank you, Pasindu!
Seriously.... this is the best explanation I have seen that describes the fundamentals behind neural net... not just the math!
Thank you John! :)
Clearly from someone who understands it deeply. Thank you so much Luis for sharing.
nice buildup to the reveal of how neural networks are built from smaller components. well done.
You sir have an amazing gift for clarity. This is the first time I have seen a comprehensible explanation of the hidden layers!
The best "intuition" explanation of neural nets I have seen. Now I really get the idea behind the maths and it helps tremendously! Thank you so much!
Thank you Louis-Marius, glad you liked it! :)
The best explanation of NN I encountered till today.
Dear Luis, great work. There are no words that can be described by any neural network to than what you have been doing and keep it up. May God bless you with everything you need in life.
This is the best ever explanation on the intuition behind neural networks. Thank you.
Maybe Im missing the simplest point of it all, at 20:37 how do we get the log values ? E.g. how does -log(0.1) become 2.3 (instead of 1?) and how do we get the 4.8 as a sum? What am I missing? :)
EDIT: I just realised it's a natural log (so ln(0.1) = 2.3 instead of log10)...I'll leave this up here in case someone else missed it as I did instead of deleting the question. Otherwise the best explanation on the topic ever! Thanks!
You turned the sourest lemon of my deep learning basics into a fresh lemonade. Thanks!
It has really boosted my interest in deep machine learning. Thanks!
Thank you Abhishek!
What a great entrance for a complete newbie to the the topic!!
Especially the beginning with the cake helped so much with actually getting behind the idea before understanding HOW it actually works.
Many others missed that point completely ....
Superb presentation, most people will be wondering what hidden layers are and what part they play, this clears it up of course the next question is how does one choose x or y hidden layers
This is the best explanation of NNs I have ever watched. Thankyou so much for posting such quality content.
Thanks for this excellent explanation. One question: at 17:15 what are you measuring? is it blueness? According to the probability function, shouldn't the most left-top point be scored with something close to 1.0? Why the 0.1? Points close to the top left corner are believed to be "most likely" blue, right?
That was brilliant! Thank you so much. As a statistician I understand all the bits that go into making the neural network, your explanation was the most intuitive I have ever seen of how they all come together to make a neural network.
You know those moments where you have spent ages trying to figure something out then something just clicks, and you say! "Ahhh, is that it? It is so simple". Well, your video just gave me one of those moments.
I wish I could give you more than one like.
this was THE BEST lecture that has explained neural networks. thank u!!
Very Clear Explanation! I feel comfortable moving forward with this topic!
Well done ✔
Thanks best regards from Egypt 😍
Great video. Thanks so much. This is the best explanation of neural networks I ever watched. Conceptually speaking is the “filter” of a convolutions neural network analogous to the hidden layers.
We should clone your intelligence and behavior into an AI so that it can make tutorial videos for every complex topic in the world!
I am not even kidding...
Ha ha
This is the tutorial from which anyone can understand Neural Networks.Thanks! I am going to see your other tutorials!
I can sincerely say so far this is one of the best introductions to Neural Networks, So glad I came across with this vid, Thank you Luis.
BEST EXPLANATION OF NON LINEARITY EVER EXISTED THANKS !
I had no idea what deep neuronal network. Thanks to you, I can think on how to apply this to a business case. Bravo!
By far, one of the most simple, concise explanation of deep learning and neural networks... thanks luis... appreciate your efforts !
The best 30 mins that I have spent in my life :-) Thank you for explaining such scary functions and terminologies in such a simple way!!
Good explanation for people who are new to deep learning and neural networks
Thank you Luis for explaining these complex concepts in such a clear and intuitive way.
Gracias Cesar! Me sirvio el feedback que me dieron en Colombia.
Jabril recommended this to me. I first went to giant’s neural network series and learned the bare basics. Then naturally the question came to my mind, why would we need multiple (hidden) layers of neurons. This video just blew that doubt to smithereens. Thank You!
... and this was neural network!!!! Its so intuitive and nature based. Thank you for removing the black cloth around it.
Thank you for the opportunity to gain some understanding of a subject which looks to be completely outside a completely unrelated profession but may be something that fascinates a few of us in terms of what potential it may hold if we think outside of the box. Thank you for your time and effort.
M
Thank you Rhonda! I find this fascinating too, and machine learning is definitely a field that many professions can use, so I think it should be accessible to people with all types of backgrounds, not only math/cs.
This is so good, it illustrates clearly now an n-dimensional arbitrary shape in the data can be defined by the lines specified by neuron pairs. That shape specifies something the enclosed/defined data have in common. I loved it.
Lot lot lot.... of love to this Channel.❤❤
Thank you so much for posting this video and help me a lot. When i was student, the instructor focus on backpropagation derivation and i never fully understand the concept of neural networks. Thank You Again!!
Thank you! I'm working right now on a backpropagation explanation that is clear, so if you have any ideas, let me know!
Because backpropagation is the Learning wheras this talk has nothing to do with neural learning besides the title. He constructs the layers manually.
Valentin Tihomirov
You are so wrong....
Are you done with backpropagation explanation?
Salutes from Sudan .. You are a life saver indeed ..You made it so easy for me ..Thank you and God bless you
Thank you for your message, Safa, it is an honor to hear that. Best of luck in your learning process, and if you have any questions or suggestions, let me know! :)
It is really friendly as per the title. The examples used are very appropriate and excellent. The explanation is fantastic, anyone with the interest of learning can understand. Using these simple examples I can easily make my students understand the concept of machine learning. Thanks for your good service.
Wow, seriously Wow... this video should be shown to every individual who is interested to know and learn Neural networks. unlike most of the lectures which tend to drive the AI & ML students away with complex explanations , this video brings them closer to this subject with simplifying the explanations. i am amazed at the topics covered in this video like
1: Why do we need to convert from discrete to continuous
2: what's the need of an error function
3: why neural networks are even needed and what are they
4: what are activation functions and how to make sense of it
5: hidden layers explanation
6: optimization, minimization, whats the whole point of summing the errors etc etc etc
Awesome video which i am gonna share with every AI ML enthusiast. thanks for the wonderful video @luis Serrano
this lesson is fantastic thank you
it takes me a whole afternoon to enter the field of neural network
Thank you, glad you liked it!
I really had a hard time grasping the basic concepts of the neural network by reading a couple of tutorial and articles on this topic. But this video just blew my mind. It is simply the best. Thanks a lot @luis for this awesome explanation.
Wow! Simply the "BESTEST" explanation on the concepts of non-linearity and linearity!!!!
This was so unbelievably awesome thank you. I've been struggling to understand this stuff for months and your video made it completely obvious. Thank you!!
this is by far the simplest neutral networks intro, thanks
Thank you!
first comment ever in UA-cam and was just to day that was the best ever explanation that I found so far.
Thank you Joao, that's an honor!
It is the best one I've found so far! Thank you!
This is the best explanation I found on UA-cam, thank you!
ok
excellent illustration !
Gracias Luis por compartir conocimientos con todos de manera amigable!!! Saludos desde Colombia.
Excellent video: anyone can understand with no background. 100% rating for this video.
Luis.. another great video for NN and Deep Learning... You have a knack to explain complex things in the most simplified manner....
On a second thought, it would be great if you could come up with an example (like ML Intro video) showing NN in use. Maybe you can include concepts for WEIGHTS, FEEDBACK LOOP, TERMINATION CRITERIA and so on. Once again many thanks for creating the video. Really appreciate all your efforts!
Thank you for the suggestion, Nilesh! Yes, working on a few more videos, including one where the training part is explained in more detail. Feel free to send any other suggestions you may have, always open to new ideas!
wow! I have been struggling to understand these concept since 4 months but this tutorial cleared all my confusions. Thank you so much
Hands down the best presentation on ANNs I seen so far! Thanks for the insights and clarity!
Thank you Shahnewaz!
Super helpful during my honeymoon phase of AI and deep learning
can we collab
This video helped me understand what a neural network is! Thanks for explaining it in such an easy to understand way. I would recommend it to all beginners.
Luis, very well explained. I have seen many articles and video on ML and NN. Your video provides a "deep" understanding of the basics of Neural Networks and provides insights in solving problems with them. Thank you.
This is the best Explanation that I have ever got on Neural Networks, Very awesome video, Thanks so much.
I've watched two of your videos so far. Good job dumbing it down for me. I really needed that description of how the hidden layers work.
Clear and simple, I'll check you convolutional neural networks video next. Great work!
Thanks for turning a research matter into a cartoon-like story wherein anyone's curiosity is developed and is forced to see each of your well dedicated videos. Hats off to your determination to help the research community.
Thank you for your kind words Sandeep! I enjoy understanding things in a pictorial way, and I'm glad that more people in the research community also feel this way.
Yes man. Great job teaching. I also enjoy when you share your mind through metaphors, for example, the line in the sand, and the magnifying glass. Thank you for making the video.
Thank you!
I was expecting that he would say easier at 5:32 but he said lot scarier. Too true!
Really a nice explanation of Neural Network. Thank you @Luis Serrano. It would be very helpful if you share the Lecture slide...
The best explanation I hve seen in the internet until this moment.
I like the way it is presented this complicated topic. Very effective method of simplifying the cryptic topics. Please do post such videos. Really appreciate it.
Luis - you are unique. One of the best and most simplistic way to teach AI. Great job.
Really amazing video, finally I understood what is Neural Network! you are best in explaining complex topics. Thanks for your effort
Thanks for making this video, by not using typically well known images of neural networks, it prevented a lot of mental blocks when watching other videos 🤗🤗🤗
No one:
Literally no one:
Luis Serrano: wait! I can make it simple.
Great explanation Luis.
really brilliant and amazing, I felt that I'm walking like a scientist and discover everything, really thanx
Aha!
Thank you so much for this video. Very few people on the internet can explain this
I can only echo the other comments; what an outstanding introduction to an often obscurely taught area!!! Thank you so much, Luis! Keep up the good work.