Exponentially Weighted Moving Average or Exponential Weighted Average | Deep Learning

[@studywithme6900]

Amazing. The Mathematical intuition that everyone missed from their videos can be found here. Truly Grateful.

[@rishabhvyas856]

You are great sir.. Hat's off to your efforts 🙏❤

[@rawatshubham09]

Sir, I hope u r doing well in ur recovery. God bless u for good health.

[@shuklaparth2619]

Thanks sir , get well soon

[@techtonik7]

Glad to see you back!

[@kshitizkhandelwal9348]

Great to see you back sir. Can you give an estimate as to when you'd complete this playlist?

[@soulfuljourney22]

Brilliant teaching, every concept on deep learning is explained in such a manner that even if I give my 50% attention, I am able to understand it.

[@sanjaisrao484]

Yess

[@sahilwithmathphysics8419]

You are great Sir and thanks for all your efforts

[@anushkabajpai168]

So good to see you back Sir :)

[@mahirpokar1528]

you have inverted the formula. it needs to be Vt = B(Thetat) + (1-B)Vt-1. Or you need to take the B value to be less than 0.5. Using your formulas the latest value is actually discounted and the older values get higher weightage. Correct me if I am wrong please.

[@AviKC-v9f]

correct!

[@3daudiomusic540]

Yes

[@_sochte_hai]

Sir is also correct it is not giving more weightage to lower coz b

[@ritikatanwar3013]

Thank you so much for this video. I was trying to understand EWMA since yesterday and you have told it with such ease. 😊

[@JourneytoWINover_PORN]

r u single?

[@amanranchi0007]

moody stable bandi/banda analogy was epic!!😅😅

[@pratikpatil956]

you are great, please upload at least 2 videos per week... there is huge gap between 2 videos....... please

[@rajniarora2828]

Aap Bhot Bhot acha padhate hai, I hope aapka channel bhot grow kre or aap aaisi hi video hume share krte rhe.

[@rb4754]

So easily explained as always...

[@ParthivShah]

Thank You Sir.

[@tathagatamarik282]

Great sir, awesome effort

[@RitikaSharma-wq7fq]

Thanks for doing all these videos sir , we are so gratefull

[@rockykumarverma980]

Thank you so much sir🙏🙏🙏

[@pratikchouhan1513]

you are great ❤️

[@ragrawal22984]

You explained everything so nicely

[@geekyprogrammer4831]

Take care of your health Nitish 😊

[@tanmaygupta8288]

Great sir

[@DharmendraKumar-DS]

The graphs you showed at 10.53 are incorrect. The more value of beta will cause less smoothening to the curve and vice-versa. Also, the formula to calculate EWMA is inverted. The beta is directly multiplied with the current data value not previous point EWMA.

[@EasySatistica]

sir hats off to your effort but please compelete this playlist.

[@Nipun_Chauhan]

Thx so much

[@ajitnayak2919]

god blessed you always sir🙏🙏🙏🙏🙏🙏🙏

[@SidIndian082]

Sir, EWMA code ?? not uploaded ...

[@rushikeshmalpe3715]

Get well soon

[@illumi.........7864]

At 7:40 I think theta1 = 25. Someone please confirm

[@JourneytoWINover_PORN]

theta0 is 25 which could also be equal to v0 theta1 is data corresponding to v1 which is 13

[@tonylee1868]

Yes

[@subratasaha8820]

smooth explanation.

[@pranavreddy9218]

V is the exponential weighted moving average - correct?

[@holyfacts1186]

Is formula for EWMA is fully correct ?

[@chambyalatul]

Thanks 🙏 sir.

[@rohitrannavre9382]

Sir, please make sure that there is less gap between videos.

[@aiforeveryone]

Amazing content

[@narendraparmar1631]

thanks sir ji😀

[@shanu9494]

Sir, please complete this playlist

[@abdulwahabkhan1086]

I have a doubt. You said that it gives more weight to the current observation and you also poved it at the end of the video but I am confused with this equation: v_t = β * v_t-1 + (1 - β) * θ_t which shows that it gives less weight to the current θ value and more weight to the previous one. Kindly clear this doubt.

[@ritikgupta6825]

i have the ame confusion, but you go internet and see some more formulas of this..then you will get clear that he used a reversed form,ula of the same thing ....also you see that on internet there is alhpa value that needs to be higle like 0.9 or 0.8

[@CuriousBoy3566]

Bro tell me, square of 0.9 is high or 0.9 value then you will understand because in Multiplation if decimal values increases the value becomes low this simple logic will rectify your doubt

[@mahirpokar1528]

yeah u are right he reversed the formula, that's fine but then he should've taken a B value less than 0.5 for it be consistent.

[@mohammadadnankhan2383]

Code not uploaded!

[@ketankhopade3817]

You find this concept in real world as for stocks analysis indicator name as EMA(exponential moving average).

[@sandipansarkar9211]

finished watching

[@jasonbourn29]

Thnks

[@adarshraj-ox1xr]

sir please recheck the formulation of the exponentially wieghted moving average i think it is incorrect please correct me if i am wrong thanks ❤❤

[@prajapatimihir7856]

The formula is actually correct because sir has used beta instead of alpha. (beta = 1- alpha) So if you replace beta with the 1-alpha you will get the formula which you may have seen everywhere on the internet.

[@anonymoustechnopath1138]

12:00 but bro main to padhne aya tha🙂

[@mohdabdulrahman6611]

Hello sir can you share ideas on major projects on ai , ml and deep learning

[@namanmodi7536]

Dan Bilzerian of deep learning

[@yashjain6372]

best

[@alastormoody1282]

SIR

[@CODEToGetHer-rq2nf]

God level teacher ❤️🤌🏻