Machine Learning Architectures & Techniques 2022

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ML engineering evolution 2018-2022. Transformers, GANs, few shot, transfer learning, federated learning, deep RL, self supervised, TPU, MLOps, etc.
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Thank you koosh for everything

ML 0 to 100 is the one that I'm always looking for and also I love the application of ML

Hall_of_fame
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Dear Koosh, I wanna thank you for your speech. that was great. I enjoyed your speech specially about MLOps

mahdarfshi
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Hey man. Hope you be well. Couldn't watch it. But just i wanted to say that I'm proud of you for being active adding more content for all languages.

md_master
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Great presentation, and to the point. Thank you

AIsourcerer
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Thanks for the presentation Koosh 🙌❤
I would like to learn more about graphs and the usage of them in recommendation systems. I highly appreciate if you talk more about them

sinahnyazdi
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Thanks Koosh. Could you possibly talk about TinyML or application of the edge computing in ML in future videos?

IrajAhangari
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Great topic and and info Koosh, thank you.
Would've been great if you could upload with higher quality.

SabaElahi
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Very Good....Thank you for sharing that

amirmn
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Hello Koosh, it was an amazing experience. I think we will see more application of ML in chemistry and also molecule physics, already there are some paper which solve dynamic deferential equations using deep graph neural networks. Any comments on other interesting emerging applications?

mahdi_sc
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Dear Kooshiar
Please introduce resources for studying ML 3.0
Thanks

amiresmaeilzadeh
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Great presentation! Would you please talk about recommender engines for upsale and cross sale?

Serenity_Smiles
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Thanks for valuble information. Could you teach these topics in the future?

mahmoodsetoodeh
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Thank you. Can I, as a graphic designer, combine part of a machine learning with a graphic design? Has anyone done this before?

grafixer
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That was a great presentation.
Are you considering any video about NLP and transformers in proteins and genetics in any time for future?
Thanks

memardi
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How do you see codex open Ai in the coding environment? I recently got access to it and it makes me suspicious about continuing learning ml languages for the sake of time?
Furthermore, I am in the architecture and building industry with a focus on energy consumption, which is basically using supervised learning; how do you see breakthroughs in the less agile industry?

imansheikhansari