4.7 Stacking Technique in Tamil

I have discussed about basics of stacking with example.
Link for PPT
drive.google.com/drive/folder...

[@rahuldhoni7]

Meanwhile rahul watching rahuls interview prediction to pass aiml exam 😂

[@because2022]

Hehehe..

[@krishnakumarik208]

Good work. Add few problems when u have time

[@because2022]

Thanks. The problem is we dont have much problems in the foreign author book. If you have some specific problems please mail to me [e-mail]

[@TheQueen-oj7os]

Thank You Sir for this understandable ensemble learning ❤

[@because2022]

Most welcome keep learning.

[@TheQueen-oj7os]

@@because2022 🤍

[@nquanta1548]

Thanks for this video 🔥🎊👏

[@because2022]

Most welcome. Keep learning and keep sharing with your friends and juniors.

[@kalairoxan2398]

Thank you sir ❤

[@because2022]

Welcome

[@zeus999ff3]

Avanga mam thana bro 🙄

[@darksoul46-hq6yw]

Easily understood sir ❤

[@because2022]

Do well.

[@yathindrapravanant.v945]

Sir...first data 70,20 ku YES NO YES vandhuchu...so ground truth yes uh
so second data 80,30 ku enna predictions varum?

[@because2022]

No Yathindra. Ground truth is always from table. For new training data alone, we take predictions from all models then include ground truth also.

[@Keelvengai_Nadu]

Mam ippa model 2 la no result varutha atha base panni tha new traing data form pananuma

[@because2022]

We create new data based on output frm all models.

[@malarkodi720]

Sir advanced ensemble technique la blending nu innoru concept iruku adhu teach panalaya sir?

[@because2022]

Hi Malarkodi, it got missed. You can refer this. www.scaler.com/topics/machine-learning/blending-in-machine-learning/ . You can let me know if you dont understand. Then we can discuss.

[@malarkodi720]

@@because2022 thank you sir

[@SivaSelvaraj-fu4wf]

​Sir aana anna university syllabus lah blending illa aama thaana sir​@@because2022

[@SyedRasheed-rc6zp]

9:37 sir boosting use panna overfitting nadakum sonninga overfitting na excellent ta work aagum la sir...adhuku yen sir namma boosting use panni reduce pannurom adhu nalla dhana sir work aagudhu aprm yen use pandrom

[@because2022]

It will work well only on training data and not on any new data. Thats why.

[@Usadreamerok]

Over fitting means not enough training dataset its a negative thing bro

[@because2022]

@@Usadreamerok It need not mean about amount of training data.