I'm a beginner in machine learning and I've been following your videos for a while now. I really appreciate your pedagogical approach, thanks for your time and the quality work you create for us for free.
Because of the way you handled it, I truly paid attention to the lecture as a research scholar from the first second to the last 51 minutes. hope I am expecting quantum CNN based lecture... Thank you ...
Thank you so much for your algorithm book, ML book, and all your videos on this channel and the previous channel. I have been a follower since 3 years ago.
I really love the power of simplicity when explaining stuff. Is there a way you can teach Confusion matrix, accuracy, precision, recall and f1 score? :)
@@SerranoAcademy thank you! Glad it is already there. You have been a critical item for me why i am loving machine learning! The intimidating machine learning and statistics terms, you made it kindergarten friendly! More powers!
Thanks, great question! They can be entangled in any way. For example, if you have the state |00> + |11>, then when they're measured, they're either both in state |0> or both in state |1>.
This and your whole series of attention NN is a thing of beauty! There are many ways of simplifying this here, but you come the closest to understanding Attention NN and QC are identical and QC is much better. In my opinion QC has never been done correctly, the gates are too confusing and poorly understood. QC is not still in simplified infant stage, it is mature what QC can do and matches all Psychology observations. All problems in Biology and NLP are sequences of strings.
Luis, complements on exceptional presentation style. I have seen many of your super videos on stats and now I am running through your ML. As always you are fantastic. Do you have any course work on Udemy?
Thank you, glad you liked it! (sorry for the super late reply). I have some courses in Coursera: on math for ML and on LLMs: www.coursera.org/instructor/luis-serrano
Hello Sir, all your lectures are very good and can be understood very well. I request you to make video on Federated machine learning, is it trending ?
Thank you Elizabeth, that's a great idea! I'm looking for topics, so I'll add it to the list. In the meantime, the best explanations of federated learning that I've seen are done by Andrew Trask, for example this one: ua-cam.com/video/4zrU54VIK6k/v-deo.html
Hi. Thanks for the video. Very interesting. I have to make a little critic though: you are equating "machine learning" with "neural networks" the whole time. I know, is a fine distinction, but ML is much bigger than NN. You can do ML with just linear regression, without NN. You should say "neural networks". And one tip: the sound in different parts of the video is at different volume. Not a bit difference, not very annoying, but just would be nice to have it all in one volume. Please don't take the critic negatively. I know you put a lot of work in the videos! Thanks for that.
This course on quantum ML is a pretty good way to get started: ua-cam.com/play/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg.html Also here there are some good coding tutorials: pennylane.ai/qml/demos_qml.html
![Lp. Сердце Вселенной #60 РОЖДЕНИЕ ЛОЛОЛОШКИ [Финал] • Майнкрафт](http://i.ytimg.com/vi/YoR0pAV9FVQ/mqdefault.jpg)
I'm a beginner in machine learning and I've been following your videos for a while now. I really appreciate your pedagogical approach, thanks for your time and the quality work you create for us for free.
Thank you for your kind words Bernard, I'm glad you like them! I have a lot of fun making them. :)
Always the best in simplifying complex concepts. Thank you.
Absolutely brilliant red blue glove experiment and how observation changes values. 🎉
Because of the way you handled it, I truly paid attention to the lecture as a research scholar from the first second to the last 51 minutes.
hope I am expecting quantum CNN based lecture...
Thank you ...
Thank you so much for your algorithm book, ML book, and all your videos on this channel and the previous channel. I have been a follower since 3 years ago.
Thank you for your kind message, I'm so glad you like the material! :)
Exciting. A conceptual journey. 🎉
Really nice...
Great finish! I have trained a few models. I understood conceptially.
I really love the power of simplicity when explaining stuff.
Is there a way you can teach
Confusion matrix, accuracy, precision, recall and f1 score? :)
Thanks Alvin! Yesss, they're all in this video! ua-cam.com/video/aDW44NPhNw0/v-deo.html
@@SerranoAcademy thank you!
Glad it is already there.
You have been a critical item for me why i am loving machine learning!
The intimidating machine learning and statistics terms, you made it kindergarten friendly! More powers!
Thanks. I really had a FOMO. Best of luck❤
Like Always Excellent Video ..👌On point Visuals & descriptions 👏Thank you so much
such a great channel. Enjoy watching it! also excellent job on coursera course for mathematics for machine learning!
Amazing! Tku sir for providing these invaluable videos🤓🥳😎
Thanks, this is great video as always.
amazing explanations.
Amazing video. Very impressed.
Thanks for another brilliant video. But shouldn't entangled qubits have exactly opposite spins? (just like entangled particles in QM)
Thanks, great question! They can be entangled in any way. For example, if you have the state |00> + |11>, then when they're measured, they're either both in state |0> or both in state |1>.
@@SerranoAcademy got it, thank you!
This and your whole series of attention NN is a thing of beauty! There are many ways of simplifying this here, but you come the closest to understanding Attention NN and QC are identical and QC is much better. In my opinion QC has never been done correctly, the gates are too confusing and poorly understood. QC is not still in simplified infant stage, it is mature what QC can do and matches all Psychology observations. All problems in Biology and NLP are sequences of strings.
Luis, complements on exceptional presentation style. I have seen many of your super videos on stats and now I am running through your ML. As always you are fantastic. Do you have any course work on Udemy?
Thank you, glad you liked it! (sorry for the super late reply). I have some courses in Coursera: on math for ML and on LLMs: www.coursera.org/instructor/luis-serrano
Hello Sir, all your lectures are very good and can be understood very well. I request you to make video on Federated machine learning, is it trending ?
Thank you Elizabeth, that's a great idea! I'm looking for topics, so I'll add it to the list. In the meantime, the best explanations of federated learning that I've seen are done by Andrew Trask, for example this one:
ua-cam.com/video/4zrU54VIK6k/v-deo.html
@@SerranoAcademy Thank you Sie
Thank you Sir
I know Quantum computing very well but not know in ML but want to do Quantum ML , how can i start??
Great question! This course is my favorite for QML: ua-cam.com/play/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg.html&si=vjjWlrXseWP99sES
Hi. Thanks for the video. Very interesting. I have to make a little critic though: you are equating "machine learning" with "neural networks" the whole time. I know, is a fine distinction, but ML is much bigger than NN. You can do ML with just linear regression, without NN. You should say "neural networks". And one tip: the sound in different parts of the video is at different volume. Not a bit difference, not very annoying, but just would be nice to have it all in one volume.
Please don't take the critic negatively. I know you put a lot of work in the videos! Thanks for that.
how do I move from ml engineer to quantom ml engineering?
This course on quantum ML is a pretty good way to get started: ua-cam.com/play/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg.html
Also here there are some good coding tutorials: pennylane.ai/qml/demos_qml.html
Why aren’t you posting more videos ?
What's happening to the other 2 lectures ?
The second one is here: ua-cam.com/video/oi5GQvJzy5I/v-deo.htmlsi=xDyPEihNyhLPZcaA
The third one I haven’t done yet… hopefully soon!
@@SerranoAcademy Thank you.
Amazing
Thank you 🤩
:)
Schrodinger's cat vibes 🐈
Lol! Alive or dead? :D
dawg...what is this music lmaoo
good lecture tho!