ML & DL Explained

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@KomalRathore-l6f 5 күн бұрын

Easy to understand

@lambdacalculus8316 12 күн бұрын

Thank you so much for explaining these ideas with this concise video.

@heyman620 17 күн бұрын

Hum, usually with anything related to correlation you do not need to scale, you normalize stuff. Look at the equations, I think it does not matter because of the math? I might be wrong. Good video!

@yagneshm.bhadiyadra4359 Ай бұрын

Thanks!

@matthewpublikum3114 Ай бұрын

Isn't the random node, e, used here is to parameterize the latent space with e, such that the user can explore the space with e?

@PiyaliKarmakar-z5n Ай бұрын

great explanation!

@joshuat6124 Ай бұрын

Thanks for the video ,subbed!

@sailfromsurigao Ай бұрын

very clear explanation. subscribed!

@JoseAnderson-c8w Ай бұрын

Mertz Vista

@abdealiarsiwala5485 2 ай бұрын

Amazing explanation! Cleared my confusion.

@guetsenelson2792 2 ай бұрын

Thanks for taking Time and explaining so well

@franzmayr 2 ай бұрын

Great video! Extremely clear :)

@lockdown-vq5bz 2 ай бұрын

Hi is this the cpu version? If so, where do we get the gpu version and could you just explain it in a bit?? Thanks

@openroomxyz 2 ай бұрын

Thanks for explenation

@RezaGhasemi-gk6it 2 ай бұрын

Perfect!

@houstonfirefox 2 ай бұрын

Great video! Suggestion: Normalize volume to 50% going forward as I really had to crank up the speakers to hear your voice.

@leu2304 2 ай бұрын

Great explanation please do more video like this

@AlaraSutcu 3 ай бұрын

Very informative, thank you

@shubha07m 3 ай бұрын

This is the best video ever explaining the GAN loss, huge thanks!

@AmitEisenberg-y5n 3 ай бұрын

Thx for the explanation! It was very clear

@tonglang7090 3 ай бұрын

super clear explained, thanks

@namelessbecky 3 ай бұрын

Thank you. This is much understandable than my textbook

@AkashaVaani-mx7cq 3 ай бұрын

Great work. Thanks...

@tesfatsion2004 3 ай бұрын

Stunning!!

@AmitEisenberg-y5n 3 ай бұрын

Thank you! Great explanation

@ganeshy574 4 ай бұрын

thanks

@kvnptl4400 4 ай бұрын

I've gone through many videos about GAN loss, but only this one explains it clearly. The only video you need to understand GAN loss. Thanks, ML Explained channel! 💌

@fact6360 5 ай бұрын

Brilliant.

@Tinien-qo1kq 5 ай бұрын

it is reaally fantastic

@sahand7798 5 ай бұрын

Wrong formula

@vkkn5162 6 ай бұрын

your'e voice is literally from Giorgio by moroder song

@adityategar6178 6 ай бұрын

My input always read (N, Hin, Win, Cin). How can i fix it to (N, Cin, Hin, Win)?

@carlosgruss7289 6 ай бұрын

Very good explanation thank you

@wodniktoja8452 6 ай бұрын

dope

@AshishOmGourav 6 ай бұрын

Helpful

@xiangli1133 7 ай бұрын

Thanks a lot!

@Qdkdj 7 ай бұрын

Thank you！

@aristotlesocrates8409 7 ай бұрын

Excellent explanation

@moatzmaloo 7 ай бұрын

Thank you

@wilsonlwtan3975 7 ай бұрын

It is cool although I don't really understand the second half. 😅

@OgulcanYardmc-vy7im 8 ай бұрын

thanks sir.

@s8x. 8 ай бұрын

WOW! THANK U. FINALLY MAKING IT EASY TK UNDERSTAND. WATCHED SO MANY VIDEOS ON VAE AND THEY JUST BRIEFLY GO OVER THE EQUATION WITHOUT EXPLAINING

@Gan-tingLoo 8 ай бұрын

Thanks for the video! I believe for the group example, the input sample is (8x5x5) instead of (8x7x7)

@shravan6457 8 ай бұрын

Very helpful. Thank you 🙏. Question. On the last plot in the video how to interpret that one SHAP red observation (at around -4 value) of the Age feature? Is that a potential outlier?

@balintfurmann5560 8 ай бұрын

Great video, made me understand the CNN-s in Python much better. Thank you!

@КириллКлимушин 8 ай бұрын

I have a small question about the video, that slightly bothers me. What this normal distribution we are sampling from consists of? If it's distribution of latent vectors, how do we collect them during training?

@aaomms7986 8 ай бұрын

Thank you this is the best explanation ❤❤❤

@andrefurlan 8 ай бұрын

Thanks! More videos please!

@andrefurlan 9 ай бұрын

Thank you a lot! I finally understood from where all these filters comes!

@muhammadanasali7631 9 ай бұрын

Can I have these slides please within respective concern 🙏💓

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