All those people who say, "Math is useless and you don't use it in the real world" are about to be replaced by machines running on all the types of math people tend to hate.
Yo Siraj, this was a awesome and simple video. I think you have figured out the best combination of pacing, math, animations, and memes now. I would appreciate if you made more videos like these on topics like decision trees, SVM, back propagation, etc. I know you have covered these topics before but I feel the quality of videos now is a lot better for learning. Like there is a huge difference between this video which you can really learn from and your "backpropogation in 5 minutes". Anyways I will submit for the challenge for this week, looking forward to other submissions as well.
this guy is not crazy at all, after 1 day of watching videos(far more fun and efficient than articles) I understand almost everything, say 80% being ML calculus and back propagation the hardest. That being said I know nothing about calc so it's a bit harder for me to grasp the concept, anyone familiar should have no problems. Next challenge is to fully understand the calcs behind and then python the stuff. Great channel!
This man is a charlatan and has not the first idea of the maths behind machine learning. He famously plagiarised a paper on AI and, do avoid getting caught like a naughty child he changed "logic gate" to "logic door" and complex Hilbert space to complicated Hilbert space. He didn't know what the basic component of a computer is or that a complex number is a number with a rational and irrational component. There are some great channels covering the maths of machine learning (eg Khan Academy) - this is not one of them.. Your grandmother knows more about math than this fraud.
Am currently learning Python to assist in corpus analysis within linguistics, everytime i get bored or demotivated I watch one of your videos to see what it is that programming can do and I get back to work. Thanx.
I haven’t seen anyone explaining the use of math in such a wonderful way for machine learning until now. If you could make the Andrew ng ML and DL series with python .. I will be the first to join and I am pretty sure everyone here will join . I really need a course which covers everything overall man .. right from math to programming to algorithms ... you never get the right structure anywhere and investing time that way is tough man given the time I have daily .. working and studying after 9pm is tough.. I wanna invest 2 hours of my day for this, if there is a well structured course available. I really wish you do this whole thing.
Thank you Siraj for the clear, accurate, concise and enlightening overview of machine learning. It answers my most fundamental question that is always on my mind, viz., Why am I doing what I am doing? Thanks again!
Man, this is the video which made me really understand where i am standing (in terms of learning) and what needs to be learnt more. Came as a motivation for me. :) :)
Math is Fun, and Calculus is the "Great Divide" between those who can do Science, and those who are just screwing around. When I hire people, the first question is "Do you know Calculus?", then a problem, even for social science positions.
Spot On, Siraj, I have seen many blogs/videos but this one, was exactly, what I was looking for. Request you to please make 2 or 3 videos with different examples with more explanations. And one suggestion/Initiative for you, can you create one page/website/your channel, where like minded people and your fans (We) can post queries and get solutions by you or your fans ? Its just a thought. Thanks.
Absolutely beautiful explanation of where different disciplines come in to solve a real Machine Learning problem - especially since I was looking for an apartment around NYC :) . Thank you so much for this!
Wow!! I have been studying machine learning for quite a while, and you my friend have just summarized the main aspcts of it, in a simple and precise explanation. Of course, talking only about supervised learning :)
Siraj, I love your videos, I watch them with subtitles because I am learning English still😀, I intend to enter this area in the future. Congratulations 👏👏😊
Monica Rocha Ora, ora, uma br aqui...E aí, como que está os estudos? Atualmente também tô querendo entrar nessa área de Machine Learning, se puder dar umas dicas ficaria agradecido kk
Wow, it's the first time I see your videos. You are doing an awesome job here. The world needs more people like you. Thank you very much for doing this.
Hi - a very informative and succint video of how these 4 areas of maths come together to lead to Machine Learning - thanks, Siraj! I am now able to use back-proagation to find a solution to a predicive / regession model! Happy to share my code!
Hello! We are researchers in human-computer interaction (HCI) looking for people who have taken an initiative to recently learn Machine Learning on their own, for career, course or curiosity. Tell us here (www.surveymonkey.ca/r/SelfLearning_ML) about your experiences and any difficulties you faced while self-teaching ML and how you overcame them, and have a chance to win $50 giftcard. You can help this project by taking out 5-10 minutes to participate in our study. People from any major/background may participate. For more details, see here: www.surveymonkey.ca/r/SelfLearning_ML Please share this request with your colleagues or friends who fit this description. The survey will be open until July 20, 2020.
WoW....!!....Excellent Demonstration....looking forward for some more lessons from you on [ Statistics,Calculus, Linear Algebra, and probability] with the basis of Machine Learning and Data Engineering.....thanks...!!
Love Siraj & Sendex. It would be great if you can make a video on ,where and how ML and AI can be implemented in physical machines like robots, industries, automation etc.
Thank you so much .... Siraj .... This is the best video I have ever seen. It clearly helps in understanding basic termnology for machine learning...... Thank you so much and keep making such videos😊😊😊
Siraj, in the case of linear regression that minimizes the sum of squared errors, one doesn't need to (and in general shouldn't, due to computational cost) use an iterative algorithm. Unlike most machine learning models, this one admits a straightforward analytical solution -- that is, a closed-form formula. To find the formula for the global minimum (shown in the link below) just take the derivative with respect to the explanatory variable x (which might be a vector of variables), set it to zero, then solve it via basic linear algebra. It's easy to show (by showing positive definiteness of its Hessian) that the error function in this case is convex, so the solution to the above procedure gives a global minimum. For more details, see for instance en.wikipedia.org/wiki/Least_squares#Solving_the_least_squares_problem best
Hi friends. On this specific subject (multivariable regression) I recommend everyone to check on Professor Wooldridge's CEO salary case where you can perform a regression on many variables in order to determine how each one explains the dependent variable (CEO's salaries). Go econometrics!
This was better than many, but still its not good for beginners. I means lot of things are not told detail. I might sound totally stupid with below questions, but I am a beginner Q1. How do you get this pink line at 2:55 ? Q2. in Y=mx+b, how can X be independent ? Q3. In this video where specifically you told about the prediction that was made by algorithm we develop , and how we compare it with the correct data ?
Maths is the biggest barrier for most people (include myself) to learn machine learning! Many people just give up because they can't handle maths and programming at the same time.
Subscribed! My problem is that each of these fields is really vast, in fact you could spend years and still not be done learning statistics or linear algebra. Could someone point out some good resources to learn each one of these disciplines?
This stuff i staught in a four year degree program at most universities. But i know some Machine learning experts with a non mathematical background. The question really is how much of Stats, Probability , linear algebra and Calculus do you need to do machine learning at a practical level? Mastering these subjects is a lifelong effort...I did this stuff myself [Bsc Mathematics] and much more like Real Analysis BUT much of it is forgotten...I now eran a living from SQL , Databases and Excel.... But this is a very good video as it summarises the nitty griity with a practical example. Exellent work
So this Fall Quarter 2019, I'm getting ready to finish Calculus I in college which taught me how to work with Toolkit Functions, Derivatives, Limits, Domains, Ranges, Power Rule, Quotient Rule, Product Rule, Chain Rule, L'Hopital's Rule, and Logarithmic Properties. My question is....do I need to take Calculus II and III to be able to understand the algorithms used in Machine-Learning? Because I would much rather be taking more programming courses. I'm already familiar with some ML functions like Sigmoid, ReLu, and TanH; but I have not yet built my first artificial neural network. Personally, I enjoy Statistics more than Calculus, so I'm hoping that I don't need to take more Calc courses to be successful in this field. I've already taken Stats 1 which taught Standard Deviation, Variance, Distribution, and a few other concepts, but it didn't cover Linear Regression and my Calculus course hasn't covered Gradient Descent. If there are only a few more essential topics for the math used in ML, then I can learn on my own if I know what to study.
You need to learn more calculus in order to properly understand gradient descent, at the moment if you know python you can create Linear Regression models
@@maximind5677 Your response is not specific enough, I already have a basic understanding of Calculus fundamentals as I explained, so my question is what else do I need to learn that I can't simple google in order to understand gradient descent? Gradient Descent doesn't seem that much more complicated than any other function or tangent equation from what I read.
Thank you, I am new in this tecnical. I think I re-read theory about probability, calculus and other. Can you recommend me some books or platforms to reform these issues? please. Excellent video.
Hello! We are researchers in human-computer interaction (HCI) looking for people who have taken an initiative to recently learn Machine Learning on their own, for career, course or curiosity. Tell us here (www.surveymonkey.ca/r/SelfLearning_ML) about your experiences and any difficulties you faced while self-teaching ML and how you overcame them, and have a chance to win $50 giftcard. You can help this project by taking out 5-10 minutes to participate in our study. People from any major/background may participate. For more details, see here: www.surveymonkey.ca/r/SelfLearning_ML Please share this request with your colleagues or friends who fit this description. The survey will be open until July 20, 2020.
Kiwimaru statistics is about what already happened (past and present), and making insights from that.. probability is about making predictions (future)
Siraj, learning machine learning with you is really easy. I really really love your content and thus I started supporting you on Patreon. Are you still posting content in that platform? I would love to know that in order to raise up my pledge to be able to have a direct conversation with you sometimes. My best wishes man and keep up the good work.
All those people who say, "Math is useless and you don't use it in the real world" are about to be replaced by machines running on all the types of math people tend to hate.
Tell 'em
@Lukas 96 This is not a threat, this is an *warning*!
I'm beginning to understand why I learnt these maths in high school.
@@morpheus7422 And I started to regret because I skipped those classes in the Highschool
😂
Yo Siraj, this was a awesome and simple video. I think you have figured out the best combination of pacing, math, animations, and memes now. I would appreciate if you made more videos like these on topics like decision trees, SVM, back propagation, etc. I know you have covered these topics before but I feel the quality of videos now is a lot better for learning. Like there is a huge difference between this video which you can really learn from and your "backpropogation in 5 minutes".
Anyways I will submit for the challenge for this week, looking forward to other submissions as well.
Good
This is my favourite channel to get introduced to everything in machine learning.
this guy is not crazy at all, after 1 day of watching videos(far more fun and efficient than articles) I understand almost everything, say 80% being ML calculus and back propagation the hardest. That being said I know nothing about calc so it's a bit harder for me to grasp the concept, anyone familiar should have no problems. Next challenge is to fully understand the calcs behind and then python the stuff. Great channel!
Brilliant video! Have been studying Machine Learning for a while but never knew what foundations it has been built upon. Thank you!
This man is a charlatan and has not the first idea of the maths behind machine learning. He famously plagiarised a paper on AI and, do avoid getting caught like a naughty child he changed "logic gate" to "logic door" and complex Hilbert space to complicated Hilbert space. He didn't know what the basic component of a computer is or that a complex number is a number with a rational and irrational component.
There are some great channels covering the maths of machine learning (eg Khan Academy) - this is not one of them.. Your grandmother knows more about math than this fraud.
Am currently learning Python to assist in corpus analysis within linguistics, everytime i get bored or demotivated I watch one of your videos to see what it is that programming can do and I get back to work. Thanx.
your video editing is getting much better :) i also can really tell you are working on your pacing and presentation tone. very good content.
Sentdex ❤
Could you tell me the what's the name of this vid that sentdex has uploaded?
I think that video is from Him explaining HaarCascades in OpenCV
its tensorflow obect detection video
I haven’t seen anyone explaining the use of math in such a wonderful way for machine learning until now. If you could make the Andrew ng ML and DL series with python .. I will be the first to join and I am pretty sure everyone here will join . I really need a course which covers everything overall man .. right from math to programming to algorithms ... you never get the right structure anywhere and investing time that way is tough man given the time I have daily .. working and studying after 9pm is tough.. I wanna invest 2 hours of my day for this, if there is a well structured course available. I really wish you do this whole thing.
You didn't talk about complicated Hilbert space. I'm so disappointed. 😥
Guys forgive him and stop doing so muth hell of overacting
I am literally enlightened on this subject.. i studied maths but never made sense so much! thank you!!!
"Like a nice... bowl." Killed it. Great job, Siraj!
Summery of the ML Stanford course by Mr. Ng :) Nice explanation btw..
Thank you Siraj for the clear, accurate, concise and enlightening overview of machine learning. It answers my most fundamental question that is always on my mind, viz., Why am I doing what I am doing? Thanks again!
Please include this video in your playlist of maths of intelligence. I love that playlist and watch it once in a month.
Cheers
Man, this is the video which made me really understand where i am standing (in terms of learning) and what needs to be learnt more. Came as a motivation for me. :) :)
Machine Learning is Math
Not exactly all
Math is Fun, and Calculus is the "Great Divide" between those who can do Science, and those who are just screwing around.
When I hire people, the first question is "Do you know Calculus?", then a problem, even for social science positions.
EqualConnect Coach
Show me something that doesn’t use math .....
One thing only ....
StarDagger Rihannsu
Oooh really nice info ...
For someone who wanna start working in this field
Deep
Spot On, Siraj, I have seen many blogs/videos but this one, was exactly, what I was looking for. Request you to please make 2 or 3 videos with different examples with more explanations. And one suggestion/Initiative for you, can you create one page/website/your channel, where like minded people and your fans (We) can post queries and get solutions by you or your fans ? Its just a thought. Thanks.
Absolutely beautiful explanation of where different disciplines come in to solve a real Machine Learning problem - especially since I was looking for an apartment around NYC :) . Thank you so much for this!
Wow!! I have been studying machine learning for quite a while, and you my friend have just summarized the main aspcts of it, in a simple and precise explanation. Of course, talking only about supervised learning :)
I like how you always put resources in the description. Thanks
Siraj, I love your videos, I watch them with subtitles because I am learning English still😀, I intend to enter this area in the future. Congratulations 👏👏😊
That's simple ... Just need high dedication to learn
Monica Rocha I m English teacher.. Do you want to learn English perfect?
Monica Rocha Ora, ora, uma br aqui...E aí, como que está os estudos? Atualmente também tô querendo entrar nessa área de Machine Learning, se puder dar umas dicas ficaria agradecido kk
@@jaedeepmakwana4551 Engineering *quastions* Mr English teacher? ua-cam.com/channels/RINI21jDSboANYuERxqZXQ.html
Dude I'm struggling with Induction proofs because it's been awhile since I last mathed but thank you for changing my perspective yet again.
Wow, it's the first time I see your videos. You are doing an awesome job here. The world needs more people like you. Thank you very much for doing this.
Thanks for the video 👍. I really enjoying your videos regarding ML. I have started gaining more interest in ML by watching your simple videos
Hi - a very informative and succint video of how these 4 areas of maths come together to lead to Machine Learning - thanks, Siraj! I am now able to use back-proagation to find a solution to a predicive / regession model! Happy to share my code!
Hello!
We are researchers in human-computer interaction (HCI) looking for people who have taken an initiative to recently learn Machine Learning on their own, for career, course or curiosity. Tell us here (www.surveymonkey.ca/r/SelfLearning_ML) about your experiences and any difficulties you faced while self-teaching ML and how you overcame them, and have a chance to win $50 giftcard.
You can help this project by taking out 5-10 minutes to participate in our study. People from any major/background may participate.
For more details, see here: www.surveymonkey.ca/r/SelfLearning_ML
Please share this request with your colleagues or friends who fit this description. The survey will be open until July 20, 2020.
WoW....!!....Excellent Demonstration....looking forward for some more lessons from you on [ Statistics,Calculus, Linear Algebra, and probability] with the basis of Machine Learning and Data Engineering.....thanks...!!
The best channel on youtube
Bro you are epic. I was watching your video for machine learning and it gave me an idea about beam steered radar calibration. thanks
*Clear and concise. Great content and explanation*
This just blown my brain away.. Thanks a lot Siraj
Thank you. Your channel is one of the few ones ML that I actually understand.
Love Siraj & Sendex.
It would be great if you can make a video on ,where and how ML and AI can be implemented in physical machines like robots, industries, automation etc.
No one could do this job better than you, Great job!
At 7:40, it should be “multivariable” regression rather than “multivariate” regression because the latter refers to multiple response variables.
Thank you so much .... Siraj .... This is the best video I have ever seen. It clearly helps in understanding basic termnology for machine learning......
Thank you so much and keep making such videos😊😊😊
I feel like Siraj gets me. Maths is very new essential
Thanks for your work, Siraj. Your videos and personality make learning from you a fun experience.
This is a really succinct and digestible breakdown. Props!
Siraj, in the case of linear regression that minimizes the sum of squared errors, one doesn't need to (and in general shouldn't, due to computational cost) use an iterative algorithm. Unlike most machine learning models, this one admits a straightforward analytical solution -- that is, a closed-form formula.
To find the formula for the global minimum (shown in the link below) just take the derivative with respect to the explanatory variable x (which might be a vector of variables), set it to zero, then solve it via basic linear algebra. It's easy to show (by showing positive definiteness of its Hessian) that the error function in this case is convex, so the solution to the above procedure gives a global minimum.
For more details, see for instance
en.wikipedia.org/wiki/Least_squares#Solving_the_least_squares_problem
best
How about the mathematics of all the new stuff - deep-learning/neural-nets, CNNs, RNN/LSTM, transformers/attention-networks, GPT-3, Alpha-Fold2 etc. ?
I wach your movies for like 1,5 year. Finaly I understand everything!
Hi friends. On this specific subject (multivariable regression) I recommend everyone to check on Professor Wooldridge's CEO salary case where you can perform a regression on many variables in order to determine how each one explains the dependent variable (CEO's salaries). Go econometrics!
Thanks for the idea, especially for those who are starting out.
Sounds like when someone talks about machine learning knowing only high school math
Math is the key topic in Machine Learning
Wow thanks for thr good presentation. Who loves a challenge?
ah! andrew ng's example!
Exactly! :)
My first time trying his video because I heard he was a fraud. And seeing this proved it
@@DeepTuts what did he do?
You are excellent! Superb! Graph! Animations ! Easy to understand! I'm wordless!
This was better than many, but still its not good for beginners. I means lot of things are not told detail. I might sound totally stupid with below questions, but I am a beginner
Q1. How do you get this pink line at 2:55 ?
Q2. in Y=mx+b, how can X be independent ?
Q3. In this video where specifically you told about the prediction that was made by algorithm we develop , and how we compare it with the correct data ?
🔥🔥🔥. Awesomely motivational, & enlightening. The “wizards of oz” will be so sad that you’re making the compex accessible.
🤘🏼🤓🤟🏼
The main advice is Explore MATH..👌👌👌
This is very insightful. Good start to machine learning.
ML videos are awesome, but please upload more coding videos on Distributed Systems
Please do make videos on this order exploding different regression methods... Very excellent video
Please make more videos on Machine learning and artificial intelligence. IF possible, then also on thesis related to ML.
You are awesome bro. You explain the topic in the easiest way
Maths is the biggest barrier for most people (include myself) to learn machine learning! Many people just give up because they can't handle maths and programming at the same time.
Using sk-learn, you can focus on the programming
make video on what are requirements to predict stock prices with machine learning
Awesome video. Crisp and clear.
This reminds me a lot of Giant_Neural_Network's neural network beginner series.
nice set of graph!
Sir your content is really great, Presentation is really excellent. But please give a pause to digest your words .
Yessss Siraj!! Yess! SLOWER vids!!! Excellent!! :D
Siraj you're the best
Wow
You are one of the best ML of youtube . It is so hard to find information on the russian .Good luck for your business .
Excellent Video, Siraj! Thank you!! :D
Thank you for create those video, you make learning AI so much fun and easier!
You are awesome siraj
Subscribed! My problem is that each of these fields is really vast, in fact you could spend years and still not be done learning statistics or linear algebra.
Could someone point out some good resources to learn each one of these disciplines?
This stuff i staught in a four year degree program at most universities. But i know some Machine learning experts with a non mathematical background. The question really is how much of Stats, Probability , linear algebra and Calculus do you need to do machine learning at a practical level? Mastering these subjects is a lifelong effort...I did this stuff myself [Bsc Mathematics] and much more like Real Analysis BUT much of it is forgotten...I now eran a living from SQL , Databases and Excel.... But this is a very good video as it summarises the nitty griity with a practical example. Exellent work
So this Fall Quarter 2019, I'm getting ready to finish Calculus I in college which taught me how to work with Toolkit Functions, Derivatives, Limits, Domains, Ranges, Power Rule, Quotient Rule, Product Rule, Chain Rule, L'Hopital's Rule, and Logarithmic Properties. My question is....do I need to take Calculus II and III to be able to understand the algorithms used in Machine-Learning? Because I would much rather be taking more programming courses. I'm already familiar with some ML functions like Sigmoid, ReLu, and TanH; but I have not yet built my first artificial neural network. Personally, I enjoy Statistics more than Calculus, so I'm hoping that I don't need to take more Calc courses to be successful in this field. I've already taken Stats 1 which taught Standard Deviation, Variance, Distribution, and a few other concepts, but it didn't cover Linear Regression and my Calculus course hasn't covered Gradient Descent. If there are only a few more essential topics for the math used in ML, then I can learn on my own if I know what to study.
You need to learn more calculus in order to properly understand gradient descent, at the moment if you know python you can create Linear Regression models
@@maximind5677 Your response is not specific enough, I already have a basic understanding of Calculus fundamentals as I explained, so my question is what else do I need to learn that I can't simple google in order to understand gradient descent? Gradient Descent doesn't seem that much more complicated than any other function or tangent equation from what I read.
siraj is definitely the best mentor
BlackReaper cheerleader *
yeah lol
BlackReaper no Buddha is. Siraj is prolly 3rd best
memetor
lmao
Excellent. Thanks
Thanks siraj..do you know paresh raval....renowned indian actor and comedian
Love you sentdex !
Very helpful videos, thank you
"Cup it like a nice ... bowl" Lmao xD
Siraj congratulations!
Great Job, It was a simple explanation and clear...
Thank you, I am new in this tecnical. I think I re-read theory about probability, calculus and other. Can you recommend me some books or platforms to reform these issues? please. Excellent video.
0:52 "It isn't or is it?"
*Vsause music kicks in*
The video was really helpful man. Thanks a ton..
as he muscle mass goes up, hes hair gets less, more much DHT siraj, look into that, love you
Y = an estimate, first line you draw already was the estimated, but should be the average, because you didn’t apply sum of least squares for that
Siraj Raval
Excellent introduction. Can you just keep building on this material?
These are some really good animations.
the memes are so cool I kept rewinding to read again
This stuff must be in my Economics school subjects program
U really make videos that are very useful
I am getting crazy about the Maths, it's so much harder than programming, I am thinking to quit my current job to learn it full time.
Nice.. btw do you have any playlist in which you teach all the math required for ml? Or give me some references from which I could learn it?
Hello!
We are researchers in human-computer interaction (HCI) looking for people who have taken an initiative to recently learn Machine Learning on their own, for career, course or curiosity. Tell us here (www.surveymonkey.ca/r/SelfLearning_ML) about your experiences and any difficulties you faced while self-teaching ML and how you overcame them, and have a chance to win $50 giftcard.
You can help this project by taking out 5-10 minutes to participate in our study. People from any major/background may participate.
For more details, see here: www.surveymonkey.ca/r/SelfLearning_ML
Please share this request with your colleagues or friends who fit this description. The survey will be open until July 20, 2020.
Omg you are better than most of my professors
Subscribed. Great Video!
Statistics and computer science can do cool things
Congratulations very good, your English is perfect, your videos are very informative
From Brasil
wow this is what i have been waiting for .. great work id become a patron but, i allready am. maybe i raise my contribution
Question: What's the difference between probability and statistics? I've always thought that probability is a subclass of statistics.
Kiwimaru statistics is about what already happened (past and present), and making insights from that.. probability is about making predictions (future)
I suggest reading about it on e.g wikipedia rather than trusting random youtube comments
Siraj, learning machine learning with you is really easy. I really really love your content and thus I started supporting you on Patreon. Are you still posting content in that platform? I would love to know that in order to raise up my pledge to be able to have a direct conversation with you sometimes. My best wishes man and keep up the good work.
Cup it firmly in your hand.. like a nice... .. bowl - Siraj, 2018
Can you make a video on Kriging (KG) Method for parameter estimation?
Thanks really awesome thank you appreciate the time you're taken to educate and teach and share your knowledge man, thanks bro so awesome!