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.
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.
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!
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?
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: ru-vid.com/group/PLmRxgFnCIhaMgvot-Xuym_hn69lmzIokg Also here there are some good coding tutorials: pennylane.ai/qml/demos_qml.html
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: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-4zrU54VIK6k.html
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>.
The second one is here: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-oi5GQvJzy5I.htmlsi=xDyPEihNyhLPZcaA The third one I haven’t done yet… hopefully soon!
