Special thanks to Dr. John Quintanilla from the University of North Texas for his inspiring lectures that first got me excited about Probability and Statistics! Thanks Dr. Q!
Thank you so much Dr. Steve for your continued efforts as a community I can't say enough how much we need more people like you. We truly appreciate your channel and the time you put in. ❤ I also love your teaching style and find it very unique and effective 😊
Probability is the probability of the data given the parameters. Statistics is the probability of the parameters given the data. This is such a hugely helpful framing for me.
Honestly the best introduction to a truly essential branch of mathematics- widely used in engineering and physics modeling. All of modern technology and advancement of our understanding of how nature behaves are a direct result of the discovery and application of this field of mathematics, a product of astounding human ingenuity. Probabilistic modeling is a powerful mathematical tool that truly shines a light on developing practical solutions to otherwise intractable problems owing to the complexity of nature and human behavior. The most profound feature and remarkable gift of nature is that nearly all complex processes are imbued or characterized by a remarkably small set of numbers (statistical properties e.g., mean, variance, correlation) that tend to exhibit a surprising high degree of predictability. These properties can therefore be exploited to extract useful information to make decisions and reveal relationships among quantities (random variables) that would otherwise be hidden from view of a naive observer looking at raw data without the aid of Probability and statistics.
People in science don't understand this enough. If you have the knowledge and experience this it's a moral obligation to share it. Imo people like you is the reason why we still have hope in this dark modern world. A lot of respect and appreciation.
@@tuongnguyen9391 I asked myself the same question before commenting. Maybe this is exactly what makes sharing knowledge in such format great that they are doing it with free in terms of money! But I am sure the satisfaction of sharing knowledge and knowing that you are contributing to the world positivity is much more satisfying than money.
I disagree that is a moral obligation, not such thing like that this is pure love and art of teaching, but the professor has no obligation, it is like teliing You have to do your work for free for the community which is of course a laudable endevour but not an obligation for anyone
@@tuongnguyen9391 I understand it is subjective but definitely He could choose whether or not to do it and each case would be totally fine and We should respect that decision
I have a bachelors in math and a masters in data science, so technically I should be familiar with these things, but I don't feel like statistics ever clicked with me in the same way the other basic areas of maths did. Really looking forward to your lecture series on this.
I have a bachelor‘s degree in Mechanical Engineering and I have also struggled with these topics. However, I understand how useful these concepts are to better understand and predict real world situations. I look forward to this course. Hopefully I get a better grasp these concepts.
Your comment has made me realize that Calculus is honestly way more intuitive imo than statistics. Crucially, calculus can rely on physics for a steady stream of examples and analogies that people can perhaps understand more easily than pure written theory. Kinematics is a great resource for calculus intuition
I love that probability and statistics is getting some spotlight. In electrical engineering, people are often more familiar with calculus, algebra, differential equations and all that jazz, but probability and statistics is very sneaky and it is EVERYWHERE. I'm ecstatic to learn more about it and i'm glad that of all people you are doing a series on it. Thank you very much professor Brunton.
.I am now retired but I am following your lectures because I am very interested in the field of AI. Your lectures show two things thát rarely coincide by a specialist: passion for the field and the gift of a good pedagogue. Your lectures are really a pleasure. I am enjoying them. Thank you very much for your knowledge and YOUR PRECIOUS TIME.
I love that so much knowledge is freely available. I dislike that I am not a creator these days, or that I've stopped being one, from being a net creator in my youth. I'm middle aged and overwhelmed by how much there is to learn, and how much we need to know to do things well these days. It is hard to get sleep at times. I am excited and when I find time away from family, or work, I am able to dig into things and learn something new. I wish life was simpler but we can't have advanced knowledge and a simple life together. This is our curse and our blessing in the age of the internet and the age of knowledge that we live in.
Im excited for this course. Your lectures on SVD, Fourier transform, Compress sensing, control system, etc. have shaped the way I see the world.. cant wait to see something new
This is a game changer in AI content world ,these 4 heavy topics which make people run away from the core and the heart of AI and ML in single course just WOW , have no more words to say , only thank you professor for your great efforts
I can’t believe it’s friday evening, and I am finally understanding the connection between probabiltiy and statistics. How did I ever graduate, post-graduate and work without this information? Your explanation is my illumination. Thank you.
I watched the introduction out of curiosity but couldn't take my eyes off the screen. You are an awesome teacher, Steve. I am looking forward to the entire series. I appreciate that the videos are no longer than 30 minutes, the average time most people can maintain focus without losing interest.
I’m taking quantum mechanics and numerical analysis classes this semester. It’s just the right time for me to learn probability theory! Thank you so much for starting this course!
really nice overview... im an old man (0x44yo) who did really well in school but had the hardest time with probability and random procs... looking forward to revisit the whole thing.. or the hole thing.. thanks steve
Thanks for this video, Steve! It took me right back to ME564 at UW - my first class in the US 9 years ago. Your explanations on probability and statistics are as clear as ever. Can't wait for the next video in this series!
Dr. Brunton, I can't wait to go through each lecture. As someone mentioned below, Prob and Stats often takes a backseat in mechanical and aerospace engineering programs, but it's everywhere. Furthermore, it's hard to find a course or book that treats the subject at the sweet spot as far as the level of mathematical detail goes. Thank you!
prof STEVE lets fkn go!!!!!!!!! i love you!!! thank you for all your content, you helped me in vector cal and ODEs, next semester ill be watching your complex analysis lectures and to find out you recently uploaded this is so awesome
Thanks again and again for the course. Here are few things I wish if you can cover in this course: 1- Information theory is good example but it's not on list of examples. 2- Law of large numbers The course seems to be covering combinatorial aspects of theory of probability. Are you plan to cover modern formal theory of probability ? You mentioned that Probability is the Dual of Statistics, are you are aware of any formal theory states that relationship between these two topics? For example in Analysis, there is the Fundamental theory of Calculus which links Integration to differentiation.
I have a physics bachelors degree and an engineering phd. The only time I took a dedicated statistics course was in high school. It was only recently when I realized how absurd that is.
You teach awesome!! Only two requests, Can you please make a PDF of your notes and share and also please write bigger, my mom thinks I need glasses!! 🤓
You said that if the distribution is unknown it is a machine learning problem. So can we depend only on machine learning sense ML is more generic than probability distributions? What are the disadvantages of using ML for all problems? I'm really excited for this course Thank you for your effort
@@adnankhrais3207 good question. It can be really expensive to learn distributions from data, so if you have some prior knowledge about the distribution it can make things much easier. It is much easier to learn the mean and variance of a normal distribution (the only two parameters needed to uniquely specify it) than it is to learn the whole distribution from scratch.
Good morning. I just watched the first lecture and it’s very interesting, I’m looking forward to the rest of the series. I have a request, is it possible for you to scan and make the notes from Professor John Quintanilla accessible? Thanks
Have you planned for the future lectures on themes like stocchastic processe, correlation function and crosschorrelation and applications in dynamic systems?
I think your definition of the Central Limit Theorem (CLT) is a bit off. You mentioned that "any combination of the average of any distributions" might lead people to think that they can sample from different data sets. The CLT states that, regardless of the true distribution of the data, a random sample of the population, providing that the sample size is large enough, the distribution of the averages of the sample converges to normal. Unless, of course, if you're talking about the density of the sum of two or more independent variables.
Hi Prof. @Eigensteve, Thank you for this lecture. Kind request - could you make this course accessible for biologists/ life scientists too. We don’t have in-depth mathematical background mostly. So when you explain the theory please explain notations and concepts in less mathematical terms and then go to your usual method of teaching for engineers way . Thank you and looking forward to this lecture series.
Hello Dr. Brunton, I was expecting to see the symmetry topic in your "Physics informed machine learning" series. Are you done with this series? Or are you going to add videos to in that series too?
So... probability is for determining what outcome we'll get (the sample), while statistics is for determining what kind of system can generate the outcome we have (probability distribution)?
Special thanks to Dr. John Quintanilla from the University of North Texas for his inspiring lectures that first got me excited about Probability and Statistics! Thanks Dr. Q!
When's the course coming out?
Thank you so much Dr. Steve for your continued efforts as a community I can't say enough how much we need more people like you. We truly appreciate your channel and the time you put in. ❤ I also love your teaching style and find it very unique and effective 😊
Thank you Dr. Brunton for another brilliant course! It means a lot!
Is this beginner friendly though?😊
can we get a pdf copy of your notebook? Thank you
Probability is the probability of the data given the parameters.
Statistics is the probability of the parameters given the data.
This is such a hugely helpful framing for me.
Honestly the best introduction to a truly essential branch of mathematics- widely used in engineering and physics modeling. All of modern technology and advancement of our understanding of how nature behaves are a direct result of the discovery and application of this field of mathematics, a product of astounding human ingenuity. Probabilistic modeling is a powerful mathematical tool that truly shines a light on developing practical solutions to otherwise intractable problems owing to the complexity of nature and human behavior. The most profound feature and remarkable gift of nature is that nearly all complex processes are imbued or characterized by a remarkably small set of numbers (statistical properties e.g., mean, variance, correlation) that tend to exhibit a surprising high degree of predictability. These properties can therefore be exploited to extract useful information to make decisions and reveal relationships among quantities (random variables) that would otherwise be hidden from view of a naive observer looking at raw data without the aid of Probability and statistics.
well said daniel
I agree. It really is the bridge between the continuous and the discrete. Very much looking forward to watching this series.
People in science don't understand this enough. If you have the knowledge and experience this it's a moral obligation to share it. Imo people like you is the reason why we still have hope in this dark modern world. A lot of respect and appreciation.
But who will paid for it
@@tuongnguyen9391 I asked myself the same question before commenting. Maybe this is exactly what makes sharing knowledge in such format great that they are doing it with free in terms of money! But I am sure the satisfaction of sharing knowledge and knowing that you are contributing to the world positivity is much more satisfying than money.
@@tuongnguyen9391 same as open source - for those who are passionate about it
I disagree that is a moral obligation, not such thing like that this is pure love and art of teaching, but the professor has no obligation, it is like teliing You have to do your work for free for the community which is of course a laudable endevour but not an obligation for anyone
@@tuongnguyen9391 I understand it is subjective but definitely He could choose whether or not to do it and each case would be totally fine and We should respect that decision
I have a bachelors in math and a masters in data science, so technically I should be familiar with these things, but I don't feel like statistics ever clicked with me in the same way the other basic areas of maths did. Really looking forward to your lecture series on this.
I have a bachelor‘s degree in Mechanical Engineering and I have also struggled with these topics. However, I understand how useful these concepts are to better understand and predict real world situations. I look forward to this course. Hopefully I get a better grasp these concepts.
Your comment has made me realize that Calculus is honestly way more intuitive imo than statistics. Crucially, calculus can rely on physics for a steady stream of examples and analogies that people can perhaps understand more easily than pure written theory. Kinematics is a great resource for calculus intuition
I love that probability and statistics is getting some spotlight. In electrical engineering, people are often more familiar with calculus, algebra, differential equations and all that jazz, but probability and statistics is very sneaky and it is EVERYWHERE. I'm ecstatic to learn more about it and i'm glad that of all people you are doing a series on it. Thank you very much professor Brunton.
.I am now retired but I am following your lectures because I am very interested in the field of AI.
Your lectures show two things thát rarely coincide by a specialist: passion for the field and the gift of a good pedagogue.
Your lectures are really a pleasure. I am enjoying them.
Thank you very much for your knowledge and YOUR PRECIOUS TIME.
I love that so much knowledge is freely available. I dislike that I am not a creator these days, or that I've stopped being one, from being a net creator in my youth. I'm middle aged and overwhelmed by how much there is to learn, and how much we need to know to do things well these days. It is hard to get sleep at times. I am excited and when I find time away from family, or work, I am able to dig into things and learn something new. I wish life was simpler but we can't have advanced knowledge and a simple life together. This is our curse and our blessing in the age of the internet and the age of knowledge that we live in.
I'm glad now everyone mention about entropy anywhere as tools for measuring uncertainty
As a PhD student in Econometrics, Im looking forward to this series on Proba and Stats!! Thank you Professor
Im excited for this course. Your lectures on SVD, Fourier transform, Compress sensing, control system, etc. have shaped the way I see the world.. cant wait to see something new
Steve is saving lives...thank you!
Hi professor Steve. I recently found your channel. This is pure gold, for free on the internet. Thank you!
This is a game changer in AI content world ,these 4 heavy topics which make people run away from the core and the heart of AI and ML in single course just WOW , have no more words to say , only thank you professor for your great efforts
I can’t believe it’s friday evening, and I am finally understanding the connection between probabiltiy and statistics. How did I ever graduate, post-graduate and work without this information? Your explanation is my illumination. Thank you.
I am beyond grateful that I found this. Can not wait for the rest of the series. 🎉
I watched the introduction out of curiosity but couldn't take my eyes off the screen. You are an awesome teacher, Steve. I am looking forward to the entire series. I appreciate that the videos are no longer than 30 minutes, the average time most people can maintain focus without losing interest.
Christmas came early this year. Thank you Dr. Brunton.
Thank you Steve! Motivation, generosity, and competence; a wonderful "distribution" of traits for this course.
Thanks Steve! Motivation, competence, and generosity; a wonderful "distribution" of traits for this course.
Thanks Steve for this new series.
May God bless you.
You definitely have me the inspiration to find out more about this branch of mathematics
Amazing amount of clarity on where we need different distributions
I am grateful to you, Professor. It is a joy to share information. specifically when our knowledge of these subjects rusts
I can't believe this. Thank you very much, professor Brunton. I'm eager for the rest of the course.
I love mathematics, If someone had taught me the way these videos do, I cannot imagine how thrilled I would've been
Thanks a lot. This can't be more helpful to refresh the memory into statistics, specially to implement them into data analysis
So looking forward to this lecture series...Dr. Brunton Thank you
I'm all in, free content as this should have an award winning, thanks a lot.
Best statistics series ever! Thank you so much
Yep, i agree!
This is honestly the best overview of stats and probability I've seen. Can't wait to start this course!
Saw this course from the Data Elixr newsletter. Amazed!!!
Thanks for watching :)
I’m taking quantum mechanics and numerical analysis classes this semester. It’s just the right time for me to learn probability theory! Thank you so much for starting this course!
keep em coming
love how concise and crisp they are
really nice overview... im an old man (0x44yo) who did really well in school but had the hardest time with probability and random procs... looking forward to revisit the whole thing.. or the hole thing.. thanks steve
We are super excited to hear that Probability and Statistics is coming out!
Thanks for this video, Steve! It took me right back to ME564 at UW - my first class in the US 9 years ago. Your explanations on probability and statistics are as clear as ever. Can't wait for the next video in this series!
My tutor Dr Andrew Blake used to say: "The calculus of uncertainty is probability".
Great video as usual other than that you look absolutely fit, I could see lot of changes from older videos. Live long our hero.
Dude this is perfect timing!! Im currently following course on this topic
Thanks Steve. It sounds a very useful
course to many students of science &
engineering. Wish you a very enjoyable
quarter. Cheers.
Many thanks!
Dr. Brunton, I can't wait to go through each lecture. As someone mentioned below, Prob and Stats often takes a backseat in mechanical and aerospace engineering programs, but it's everywhere. Furthermore, it's hard to find a course or book that treats the subject at the sweet spot as far as the level of mathematical detail goes. Thank you!
You are very welcome!
Truly inspiring and appreciate your intro, looking forward for more videos on this. Thanks
I am looking forward to this course, as this is currently big gap in my knowledge of mathematics (beyond the basics). Thank you for posting.
A top body floating and teaching!
Can’t wait, always good to top up again on fundamentals
Fantástico! I always regretted not having taken a course on probability and statistics. Now you are giving us this opportunity. Thank you.
I've been waiting for this series for years!!!
Cool! A new series! Thank you for making such nice videos!
Amazing video, I can't wait for the following videos on this topic
Your passion is our candle. Good luck.
Amazing explanations professor, I've taken a course in statistics before, but your video made some things click which didn't before, thank you!
prof STEVE lets fkn go!!!!!!!!! i love you!!! thank you for all your content, you helped me in vector cal and ODEs, next semester ill be watching your complex analysis lectures and to find out you recently uploaded this is so awesome
Thanks again and again for the course. Here are few things I wish if you can cover in this course:
1- Information theory is good example but it's not on list of examples.
2- Law of large numbers
The course seems to be covering combinatorial aspects of theory of probability. Are you plan to cover modern formal theory of probability ?
You mentioned that Probability is the Dual of Statistics, are you are aware of any formal theory states that relationship between these two topics?
For example in Analysis, there is the Fundamental theory of Calculus which links Integration to differentiation.
I cannot wait! Thank you professor!
Thank you so much, Professor! Keep up the great work✊
Also I'm glad you mentioned human behavior, yes it is complex
I have a physics bachelors degree and an engineering phd. The only time I took a dedicated statistics course was in high school. It was only recently when I realized how absurd that is.
I am so excited for this series! :D Thanks for doing this!
This comes Handy, thank you professor, un saludo desde Cancún México.
Great video. Help me a lot. Thank you so much!!!
Hi, thanks for this. I'm really looking forward to this. Do you have a schedule for releasing new videos?
Profesor Brunton,
I majored in Control Engineering at the Technical University of Dresden
Looks like a fantastic course. Thank you!
You teach awesome!!
Only two requests, Can you please make a PDF of your notes and share and also please write bigger, my mom thinks I need glasses!! 🤓
Thanks so much! Is there a recommended book to follow through for practice? Thanks
You said that if the distribution is unknown it is a machine learning problem.
So can we depend only on machine learning sense ML is more generic than probability distributions?
What are the disadvantages of using ML for all problems?
I'm really excited for this course
Thank you for your effort
@@adnankhrais3207 good question. It can be really expensive to learn distributions from data, so if you have some prior knowledge about the distribution it can make things much easier. It is much easier to learn the mean and variance of a normal distribution (the only two parameters needed to uniquely specify it) than it is to learn the whole distribution from scratch.
@@Eigensteve
I got it.
Thank you for responding.
I wouldn't say resampling is the same as Machine Learning (regression and classification)
finally a good video in youtube about probability. Thanks a lot. You are the best
Glad you liked it!
Thank you, Dr Brunton. Awesome lectures!! Is there a recommended book that I can use when following along the lectures?
Oh my oh my oh my I'm SO looking forward to this course. :3
Really looking forward to this.
Thank you.
Good morning. I just watched the first lecture and it’s very interesting, I’m looking forward to the rest of the series.
I have a request, is it possible for you to scan and make the notes from Professor John Quintanilla accessible? Thanks
Great video as always!
love your explanation sir
Well waiting for this❤
WE MAKING IT OUT OF P.S. SEMESTER WITH THIS ONE 🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥 ty btw
Kindly make a course in Linear algebra as well, Thanks for your kindness ❤
Thank you so much for this!
Looking forward to review kalman filters, the guiding dog from my sensors.
Excellent!🎉
so excited to learn
thank you
Have you planned for the future lectures on themes like stocchastic processe, correlation function and crosschorrelation and applications in dynamic systems?
Thank you
I think your definition of the Central Limit Theorem (CLT) is a bit off. You mentioned that "any combination of the average of any distributions" might lead people to think that they can sample from different data sets. The CLT states that, regardless of the true distribution of the data, a random sample of the population, providing that the sample size is large enough, the distribution of the averages of the sample converges to normal.
Unless, of course, if you're talking about the density of the sum of two or more independent variables.
Hi Prof. @Eigensteve, Thank you for this lecture. Kind request - could you make this course accessible for biologists/ life scientists too. We don’t have in-depth mathematical background mostly. So when you explain the theory please explain notations and concepts in less mathematical terms and then go to your usual method of teaching for engineers way . Thank you and looking forward to this lecture series.
I would be interested of taking this course Dr. Brunton. Will it be available on Coursera Plus?
Could you make a course for the Bayesian Statistics, please?
@@eafadeev working on it ;)
Please also cover stochastic proceses, estimators, and monte carlo methods.
Exactly when I needed it!
Hello Dr. Brunton,
I was expecting to see the symmetry topic in your "Physics informed machine learning" series. Are you done with this series? Or are you going to add videos to in that series too?
@@sagsolyukariasagi adding videos to that series too but taking a few months to do some other videos first
Thanks professor. Do you plan to cover any probabilistic programming language like pyro or tensorflow probability ?
@@vinaykulkarni4397 probably just python but not sure yet
Thaank you very much Sir.
Thank you so much!
So exciting!!
I love it from South Korea.
The 99% mathematicians in my country just read slides in their classes and forces students to cram formulas.
So... probability is for determining what outcome we'll get (the sample), while statistics is for determining what kind of system can generate the outcome we have (probability distribution)?
This is gold.
Thank you...
Hi how can I get notes of these lectures .. it will be super helpful to get aligned...
Btw thanks a lot for these beautiful lectures