Thanks for yet another incredibly informative video! I am eagerly waiting on physics informed machine learning. I would also love to see some material covering reinforcement learning in the context of a continuous state space (perhaps optimizing coefficients of a polynomial, not too different from the pseudospectral method for solving optimal control problems).
You are welcome! Physics informed machine learning is high on my list... maybe the top, of new videos to make in 2024. Will look into continuous RL too
Hi Dr. Brunton, I'm a former engineer now in the policy making space, and you're content has been so incredibly useful for me. The pacing, clarity, and the story telling has been perfect. I don't have any intentions of becoming an AI scientist or engineer, but it's helping me learn enough of the nuts and bolts I can inform decision makers and the public. A million times better than some of the machine learning crash courses on the internet.
Great start on a new series! I would be especially interested if you could cover small system implementations, such as TinyML and the optimizations needed to fit on small platforms. Keep up the good work!
That's great, thank you! On 12:41, surely we may soon get to design models that are specialised to work together in solving each element of that procedure, hence automating and creating better models than what humans could? (much like Neural Architecture search but including more branches like data collection etc)
I think the title is misleading. I doubt anyone could build an ML Model based on this video alone, despite having a title which suggests it will enable someone to build an ML Model. This video gives a high-level description of ML Models.
you said you would demystify, but the magic is how it's getting done. You just move your hands around the space where the magic happens, exactly the way magicians do. The way how it calculates is that magic that i anticipated to understand after watching the vid, but you just said it does it. But how
you are literary one of the best if not best in systems engineering / control system theory. I am very glad you are covering this
Fantastic ability to convey knowledge
You are the greatest educator for this I’ve ever seen ever and likely will continue to be, forever.
excellent overview of machine learning and the steps you need to take to build a model. Gifted speaker.
Thanks for yet another incredibly informative video! I am eagerly waiting on physics informed machine learning. I would also love to see some material covering reinforcement learning in the context of a continuous state space (perhaps optimizing coefficients of a polynomial, not too different from the pseudospectral method for solving optimal control problems).
You are welcome! Physics informed machine learning is high on my list... maybe the top, of new videos to make in 2024. Will look into continuous RL too
Hi Dr. Brunton, I'm a former engineer now in the policy making space, and you're content has been so incredibly useful for me. The pacing, clarity, and the story telling has been perfect. I don't have any intentions of becoming an AI scientist or engineer, but it's helping me learn enough of the nuts and bolts I can inform decision makers and the public. A million times better than some of the machine learning crash courses on the internet.
Thank you so much! 🙏 I'm so glad it is helpful
Great start on a new series! I would be especially interested if you could cover small system implementations, such as TinyML and the optimizations needed to fit on small platforms. Keep up the good work!
What a clarity of information. You did it the best ❤🎉. Love you dear. Keep teaching so many thanks
My mind was blown by that picasso quote ... it's a brilliant observation.
Loved how you explains ur Intuitions. Something I really want to have. 😢
a really in depth how to video…👏
Thank you for that overview, Dr.
❤❤❤شرح ممتاز دكتور ممكن ان تضيف تطبيقات عملية واكواد جاهزة من فضلك استاذ وشكرا ❤❤❤❤
When I was in high school, we had a shirt with the quote "Science is just magic without lies" on it. The quote by Clarke reminds me of that :D
That's great, thank you!
On 12:41, surely we may soon get to design models that are specialised to work together in solving each element of that procedure, hence automating and creating better models than what humans could? (much like Neural Architecture search but including more branches like data collection etc)
I think the title is misleading. I doubt anyone could build an ML Model based on this video alone, despite having a title which suggests it will enable someone to build an ML Model. This video gives a high-level description of ML Models.
thks!!! I bought your book; awesome!!
very good
Hi. Does anyone have a link to the data visualization series? I’m very curious about it. Thank you!
Seems a useful tutorial for me... 🎉
please doctor answer me is the ai powered tools will replace programmers and excuse my ignorance in this topic
Guys a genius
you said you would demystify, but the magic is how it's getting done. You just move your hands around the space where the magic happens, exactly the way magicians do. The way how it calculates is that magic that i anticipated to understand after watching the vid, but you just said it does it. But how
Thanks
'promo sm' 🙂
Too much jibberry-jabberry w/ animated hands - not enough meat to articulating in simple terms of what a model is...sorry