- Видео 127
- Просмотров 99 671
Ganesh Ramakrishnan
Добавлен 18 апр 2011
CS709 2024 Project disucssions [Part 2] 20240507 105926 Meeting Recording Part 2
CS709 2024 Project disucssions [Part 2] 20240507 105926 Meeting Recording Part 2
Просмотров: 59
Видео
CS709 2024 Project discussions [Part 1] 20240507 105926 Meeting Recording [Part 1]
Просмотров 135 месяцев назад
CS709 2024 Project discussions [Part 1] 20240507 105926 Meeting Recording [Part 1]
CS769 2024 Lec 23: Examples - Coop costs, Attr Pot, Complexity, Representation, Diversity, Coverage
Просмотров 247 месяцев назад
CS769 2024 Lec 23: Examples - Coop costs, Attr Pot, Complexity, Representation, Diversity, Coverage
CS769 2024 Lec 22: Submodular functions, equivalent definitions, basic properties
Просмотров 817 месяцев назад
CS769 2024 Lec 23: Examples of Submodular functions: Cooperative costs, Attractive Potentials, Complexity, Representation, Diversity, Coverage
CS769 2024 Lec 20: Projected Gradient Descent, Constrained Optimization and KKT Conditions, Duality
Просмотров 987 месяцев назад
CS769 2024 Lec 20: Projected Gradient Descent, Constrained Optimization and KKT Conditions, Duality
CS769 2024 Lec 19 Convergence of Accelerated Generalized GD, Projected GD, Lagrange Functions
Просмотров 367 месяцев назад
CS769 2024 Lec 19 Convergence of Accelerated Generalized GD, Projected GD, Lagrange Functions
Saundaryalakshmi Katha kathan Shivaji Maharaj Shivajayanti
Просмотров 307 месяцев назад
Saundaryalakshmi Katha kathan Shivaji Maharaj Shivajayanti
CS769 2024 Lec 18 Proximal Operator Derivation, Convergence of Generalized GD and Projected GD
Просмотров 277 месяцев назад
CS769 2024 Lec 18 Proximal Operator Derivation, Convergence of Generalized GD and Projected GD
CS769 2024 Lec 17 From Proximal GD to Generalized GD, Derivation of Proximal Operator with Examples
Просмотров 418 месяцев назад
CS769 2024 Lec 17 From Proximal GD to Generalized GD, Derivation of Proximal Operator with Examples
CS769 2024 Lec 16 Concluding SGD variants AdaGrad, RMSProp, ADAM, NADAM, AdaMax, ADADelta, AMSGrad
Просмотров 448 месяцев назад
CS769 2024 Lec 16 Concluding SGD variants AdaGrad, RMSProp, ADAM, NADAM, AdaMax, ADADelta, AMSGrad
CS769 2024 Lec 15 SGD+variants such as AdaGrad, RMSProp, ADAM with (Quasi) Newton inspiration
Просмотров 448 месяцев назад
CS769 2024 Lec 15 SGD variants such as AdaGrad, RMSProp, ADAM with (Quasi) Newton inspiration
CS769 2024 Lec 14 Accelerated GD, Subgradient Descent, Stochastic Gradient Descent & Convergences
Просмотров 798 месяцев назад
CS769 2024 Lec 14 Accelerated GD, Subgradient Descent, Stochastic Gradient Descent & Convergences
CS769 2024 Lec 13 Convergence GD for Strong Cnvxty + Lipschitz, Lower Bounds results, Accelerated GD
Просмотров 408 месяцев назад
CS769 2024 Lec 13 Convergence GD for Strong Cnvxty Lipschitz, Lower Bounds results, Accelerated GD
CS769 2024 Lec 12 Convergence GradDescent Convexity + L-continuity/smoothness (Optimization in ML)
Просмотров 559 месяцев назад
CS769 2024 Lec 12 Convergence GradDescent Convexity L-continuity/smoothness (Optimization in ML)
CS769 2024 Lec 11 Lipschitz continuity & smoothness for Optimization, ML losses (Optimization in ML)
Просмотров 899 месяцев назад
CS769 2024 Lec 11 Lipschitz continuity & smoothness for Optimization, ML losses (Optimization in ML)
CS769 2024 Lec 10 Necessary and Sufficient for opt - convexity & subgradients (Optimization in ML)
Просмотров 329 месяцев назад
CS769 2024 Lec 10 Necessary and Sufficient for opt - convexity & subgradients (Optimization in ML)
CS769 2024 Lec 9 Subgradient and subdiff calculus explained & illustrated (Optimization in ML)
Просмотров 669 месяцев назад
CS769 2024 Lec 9 Subgradient and subdiff calculus explained & illustrated (Optimization in ML)
CS769 2024 Lec 8 Quasi Convexity, Epigraphs, First and Second order conditions (Optimization in ML)
Просмотров 489 месяцев назад
CS769 2024 Lec 8 Quasi Convexity, Epigraphs, First and Second order conditions (Optimization in ML)
CS769 2024 Lec 6 Convexity: Sets, Functions, Calculus, Examples (Optimization in Machine Learning)
Просмотров 359 месяцев назад
CS769 2024 Lec 6 Convexity: Sets, Functions, Calculus, Examples (Optimization in Machine Learning)
CS769 2024 Lec 7 Calculus of Convex Fns, ML Examples, Gradient, Quasi Convexity (Optimization in ML)
Просмотров 689 месяцев назад
CS769 2024 Lec 7 Calculus of Convex Fns, ML Examples, Gradient, Quasi Convexity (Optimization in ML)
Complete Part1 संज्ञा Samskrita Sammelanam [Samvardhan Gyaankulam संवर्धन ज्ञानकुलम] January 28 '24
Просмотров 259 месяцев назад
Complete Part1 संज्ञा Samskrita Sammelanam [Samvardhan Gyaankulam संवर्धन ज्ञानकुलम] January 28 '24
Complete Part2 संज्ञा Samskrita Sammelanam [Samvardhan Gyaankulam संवर्धन ज्ञानकुलम] January 28 '24
Просмотров 339 месяцев назад
Complete Part2 संज्ञा Samskrita Sammelanam [Samvardhan Gyaankulam संवर्धन ज्ञानकुलम] January 28 '24
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 1 : 28th January 2024(1)
Просмотров 399 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 1 : 28th January 2024(1)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(3)
Просмотров 299 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(3)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 2 : 28th January 2024(2)
Просмотров 169 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 2 : 28th January 2024(2)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 2 : 28th January 2024(4)
Просмотров 179 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 2 : 28th January 2024(4)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(2)
Просмотров 139 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(2)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(5)
Просмотров 429 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(5)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(1)
Просмотров 99 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(1)
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(4)
Просмотров 169 месяцев назад
Samskrita Sammelanam Samvardhan Gnyanakulam presentation - Part 3 : 28th January 2024(4)
Thanks for uploading this excellent lecture series. So much of knowledge for free, in one place, lucidly explained. Gurumurthy sir is a visionary.
Thank you so much for sharing! What a wonderful story. Very short story but deep message.❤
P r o m o s m ✔️
Greate lecture.....🙏🙏🙏
Brilliantly expounded concepts
In two years only 3.8K views, Guru sir has put great presentation to educate current and future economist and policy makers.
Bahut Bahut Dhanyawaad
Thank you so much sir for this series. I was searching for this hopelessly. Extremely grateful to you. Jai Hind. 🙏🏽
Fantastic series!! Very grateful to you for the upload!!
The same wily Friedman on British Imperialism of India.ruclips.net/video/G7YIbfUmx2o/видео.html
1:25:15
1:28:00
1:18:32
1:32:50
Mukul Kanitkar
We don't look at world as family but the world itself is a family.
52:29
1:13:50
Thanks for uploading here
Hello, sir, have you uploaded a basic course for "Machine Learning"? Or can you give me a source from where I can brush up the algorithms/ml undergraduate courses?
Follow CS 229 by Dr Anand Avati Stanford, it's a 43 hrs exhaustive ml grad level course much better than CS 229 2018 by Dr Ng and for practice follow the assignments of the same. You can also follow the Cornell ml course by Dr Killian Weinberg or the CMU one by Dr Tom Mitchell. PRNN by Dr P S Sastry by IISc B is also an excellent course covering all the theoretical nitty gritty of ML but it's mathematically very rigorous (cover linear algebra, probability & statistics, multivariable calculus, optimization methods beforehand).
Hello,sir.Ganesh Ramakrishnan sir could you please provide the link the enotes for all the lecture videos,it would be really helpful.
What a brilliant analysis of the Asian model. Eye opening.
Extraordinary wisdom....
The legend himself in action
These indian traditional highly profitable and secure businessmen do not go for IPO to raise funds. Only huge worthless instituition like Zomato go for it with fictitious valuation!!!
The information on economics is just invaluable. Why can’t our goby to start with really implement it verbatim , later we can think internationally. Any good development should start in your own house .
I think from what you say the recent reduction in leverage by sebi is saving people and the country
I think our investment managers unnecessarily take relevance of US fed meeting, employment data and such nonsense without knowing the retail investor mentality is born in India with our own sentiments. That is why recently though fii removed nearly 40000 cr in few weeks nifty did not fall because of our retail investor. Am I right in my thinking ?
There is no relationship in contract because it is finite and basic human relations is infinite.
Cooking is done by MNCs is simultaneously funny and alarming. One in kitchen and the other the books!!?
Thank you
Thank you
Still india hungry for FDI
nzmh0 vum.fyi
🙏🏻
प्रणाम मुकुल भैया🙏🏻🙏🏻🙏🏻
docs.google.com/document/u/1/d/1uL3oVV9FPoG6fxtlYzdb2UqiyuTOpSjc4CcpyfhlUpU/mobilebasic# The lecture notes for this series can be found here.
This is GOLD!!! Thanks a lot for sharing this
The economist shot dead, is he Nikolai Kondratiev? Timeline 1:02:00
Never knew about the japanese household savings model!! Would like to read more on this
The ending answer was awesome!! We need to learn the facts
He is a genius.
aapne aanke kholi hai. bahut bahut dhanyavad
@Ganesh Ramachandran Sir, please upload more lectures of this sort! Thank you so much. _/\_
Only 4614 views? What a pity!
Maybe I am late in here, but I must say this that I am highly enlightened today. Thanks a lot. ☺️👍