Modified Newton method | Exact Line Search | Theory and Python Code | Optimization Algorithms #4

[@leila3268]

U r watching a master at work !

[@AhmadBazzi]

Glad you enjoyed it !

[@arifahmed5262]

Good job

[@habiburrehman5290]

Good job keep it up ☺️

[@ak_amazingkinggaming3238]

I don't understand why some people hating, - yes, Prof Ahmad missed a couple of symbols (once in a lifetime) but he's still the best !

[@yasindemirel7871]

Why are you dropping three videos (each about 40 minutes) a week ? Please take care of your wellbeing, Ahmad :) We love you

[@mdnishad1148]

Nice 🥰🥰🥰

[@SadManEdition]

This is the best explanation of Optimization I have ever come across. This guy is talented

[@FuadEkberov090]

I like how you make examples to explain the concepts of each method! Brilliant and easy to understand! Thank you so much!!!

[@rasxodmusic4821]

This will complete my Linear Algebra / Calculus /Optimization trio I was missing to truly understand Machine Learning.

[@enessweed251]

You are watching a master at work !!!!!!!!

[@topmusic7356]

The Convex Optimization King is back

[@vishalchandekarekachchhawa9627]

Those animations are sick af !

[@nursyazwani7757]

This and the video on the second Wolfe condition helped me understand completely the concepts and the intuition behind these criteria. Thank you very much ! Amazing explanations.

[@AhmadBazzi]

Wow Nur - glad you found them really helpful !

[@kral-brawlstars6710]

I am studying at Erasmus University Rotterdam for Non-Linear Optimization. This video helped me significantly. Thank you for your efforts.

[@razanalkado1688]

That's correct, the value shown in the video is a local minimum, and the function is unbounded for large negative x and y values.

[@JosephBenson]

Amazing lectures! I'm using these to study for my Continuous Optimization course

[@ulasyldz1344]

This guy is super underated !

[@Informationalcreator]

Brilliant! One of the best explanation to descent gradient I have ever seen. Well done man

[@ankushsharma6456]

I really like the way you explained the optimizing algorithm. love it :)

[@1twoka66]

A man before his time ❤

[@dj.emyemy8759]

This nailed down the Adam paper. Thanks alot

[@erenhd94]

My professor at Stanford recommended this channel.

[@dannycashy]

It's a good example of why it's important to understand the shape of the function you are optimizing, and one of the potential downfalls of gradient based solvers.

[@galacticgames9824]

Great introductory video. Thank you.

[@thevowtv1563]

Excellent explanations thank you! Will watch more

[@huseyinsuataydn6412]

Love from the USA !

[@volkanmaral1944]

You are a good teacher

[@oromoshow2057]

Thankyou sooo much sir for such a simple and brilliant graphical illustrations. RESPECT!!!!!

[@hdcluptr366]

your all videos are great

[@yahiabenliram8691]

This lecture was recommended by my professor at Harvard !!!!!

[@503_alexx]

Damn those animations are sick bruh !

[@arifdrgn8756]

This is incredible .. crystal clean explanations.

[@tthmidov2842]

THANK YOU DR AHMAD !

[@alionen]

Super. Content que cela soit utile. Bonne chance pour la suite.

[@tamerolur2776]

Cannot thank you enough professor Ahmad Bazzi.

[@mami3323]

WOW! Truly impressive teacher. YOU should get professors fired for not being on your level.

[@DJAYUSHOFFICIALL]

Thank you very much - that was concise, clear and easy to understand!

[@awhlvna6261]

You are so sweet. Thank you Sir, for these awesome videos!

[@galipaltnbay6308]

I hope listening to this brings more positive KZbin channels like yours 💜

[@legendpubg6590]

I was already at MIT. I must have missed you! :)

[@efraim3940]

Wonderful explanation!!

[@doruktadunya943]

Nicely done

[@filmcehennemi592]

many thanks! please upload more videos! there are very helpful, especially for students!

[@samedgaming4377]

nice tutorial good explanation tnx

[@soc1etysports767]

Thanks for the explanations.

[@vibezz_gal9010]

Great explanation..thank you

[@مطبخامريتاجوتسنيم]

Excellent video! Thank you!

[@puroporo9437]

great explanation

[@DanielyOliveira]

Thank so you much for this video, it helped me a lot

[@failoyuncu1482]

Your videos are very informative. Thank you!

[@ugh.victory]

Greetings from Canada !

[@besiktasndunyas954]

make more videos!! It was fantastic!!

[@jadolive-erdem2829]

Underrated !!!

[@AHMETCAN-hk4en]

indeed helped. Thanks for the great video

[@anuragtech1637]

سلام عليكم دكتور ممكن اسهل اوالافضل لخوارزميات ضمن ال Meta- heuristic Optimization موفقين ان شاء الله بحق محمد وال محمد

[@elekber_pubgaze6609]

Great video!

[@ramibayraktar3740]

very nice and cool

[@confusedtv]

Thanks for the great explanation oh mighty bearded one !

[@CİOzSlegzWeg]

Wow, that's an interesting approach. I hope the videos are helpful :-)

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Not fair, this guy is more underrated than Hugh Heffner !

[@eheehe7965]

highly appreciated!!

[@shiroitem8230]

Great video thanks.

[@sreerag2167]

To the viewers, I am a graduate student getting into optimization theory. And I must say this is the best explanation of the inexact line search conditions which often go by the name Armijo conditions.

[@emrebozkurt4676]

Damn. This was really good explanation

[@atakanbayar93]

thanks for give a caption, helpful!

[@aybars83]

Thank you very much, sir!

[@edanursirin4414]

Nice 👍🏽

[@hakancuval1496]

Hi Ahmad, in this context a solver is a computer program that finds the solution to an optimization problem.

[@melekzehrakara3365]

Great Video thanks

[@mertkara9165]

Love this

[@masteytv4664]

Nice video

[@LIFEOFAGAMER297]

Many thanks!

[@garyoak7462]

Followed you on LinkedIn ..

[@mdnishad1148]

Nice

[@fxriyt2206]

I just learned from a friend of a friend who knows Ahmad that he does not have a team to help him with all this 😲 Then i found the answer to my question if superheros exist.

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I like that tea-drinking always causes non-zero suffering

[@mumbaikichorisn1534]

You are my god.

[@gameking7440]

Why does Ahmad not have 1 million subscribers by now ?

[@StarMax07]

super Nice! :)

[@nekros3989]

Thank you so much for such a helpful video! May I ask what software setup you used to create illustrations and images on the screen and to edit the video?

[@huseyinhatip7066]

Nice video Ahmad. I would like to help to point out that the slope equation in 2:20 is mistyped. I hope it helps. Thanks.

[@MRGAMINGop1]

Sir please explain how to apply dataset on any one of the algorithm

[@amineslimane5152]

Thats used in optimization methods for training a machine learning model ! you need to refer to the Machine Learning course

[@wolfbeta5828]

Can you give any advise on optimization of pid conteollers using ADAM (Thank you in advance ❤️)

[@مطبخالشطورةوبس]

Why do we need correction in momentum or rms using T elimination?

[@eneserkurt1702]

This example would technically be more correct if posed as a constrained optimization problem to limit the search to just the area shown.

[@HH-nb1ou]

but we do initialize parameters beta_1 and beta_2 ?

[@takeuchikame]

hey, any ideas on what is fuzzt rule based model, lasso regression?

[@mysterchannel5613]

Wow

[@acclaros356]

Nice. Nice ! i wanna ask, what is the time complexity of any evolutionary based optimization algorithm?

[@ohiogaming_7]

Can Adam optimization be used for classification problems?

[@j.g.gaming7296]

Dear prof. Ahmad. We have proven that there exists alpha with 0 < beta_1 < alpha < beta_2 < 1 such that both Wolfe conditions are fulfilled. So why do we initialize the lower bound equal to zero and the upper bound equal to infinity. Is it not easier to set the alpha lower bound to beta_1 and the upper bound to beta_2? Best regards from Uni Heidelberg

[@umuttosun2479]

How can i get any algorithm of Ant Colony Optimization

[@gptpodcast238]

Because we do not know their value from the theory. We just know that they exist.

[@Rita-ky4wr]

(how to Calculate Convolutional Layer Volume in ConvNet)

[@gamerspkistan300]

I didn't realize he was left-handed until 03:34 lol

[@sarabrajsmusic]

Thank you God. I mean Ahmad !

[@thekoray1031]

No. Quasi-Newton method do not use the second derivatives. Only the gradient. They build a secant approximation of the second derivatives matrix. See chapter 13 of

[@marouaammine2986]

🇨🇦

[@alioter3032]

so what you're saying is, Buddha should have used ML to minimize suffering. got it.

[@perikz8679]

If Noecedal Wright confused you, this is the place to get it sorted once and for all.

[@3HarfliTas]

Great explanation. Please join MIT to help us :)

[@duhancevre2157]

Sdb = β₂Sdb + (1 - β₂)db²