Gradient Boosting for Classification | Geometric Intuition | CampusX

[@pranalipatle2215]

Sir more than thousands of people wants to give you blessings for resume your deep learning playlist again .....make sure you will help them who are eagerly looking forward

[@lfjv]

People take pride in their achievements. However, I take pride in coming across your channel and learning from you. You are the best teacher out there to learn Machine Learning from. Keep making such exceptionally good videos and keep on helping people like us who are hungry to learn more and more about ML. Every time I watch your videos, I learn A LOT. And it makes my day every single time.

[@Ifarastimon]

🌈✨ Greetings from across the border in Pakistan! Your teachings on CampusX transcend geographical boundaries and remind us that knowledge knows no borders. Your commitment to fostering an inclusive and diverse learning environment is truly inspiring

[@MalikZaheerAbbas-yj5go]

Do you enroll in DSMP course.

[@mgopalakrishnan3439]

I’m a great fan of your content, sir, and I truly appreciate the value it brings to learners worldwide in the fields of Machine Learning and Deep Learning. I have a small request: as your videos are watched by people from various backgrounds, it would be incredibly helpful if more of the content were delivered in English. This would make it easier for a broader audience, like myself, to follow along and fully benefit from your teachings. I hope that, from your upcoming series on PyTorch and Generative AI, we might see more content in English. Thank you very much for considering this suggestion!

[@stb6508]

sir please complete deep learning series

[@rereer-c6v]

Thank you so much for this in-depth explanation.

[@parometakarmmakar6620]

You are a star ⭐ who taught us how to shine ✨ Happy teacher's day sir.. 🙏🙏💐💐 Wish you all the happiness in the world😊

[@rashidsiddiqui4502]

great session sir. really deep expalaination

[@rupeshkataria81]

Sir please continue the deep learning playlist you already have explained these topic previously

[@heaven-aman5946]

Wonderful explanation as always ❤

[@piyushjain4233]

That last geometric visualization was just the best. Awesome Teaching Sir

[@FaizKhan-zu2kp]

sir please complete your deep learning series please sir

[@yeshpalsingh9272]

He is going to do it very soon bro after he ends dsmp !

[@yeshpalsingh9272]

* Nitish Sir

[@edgyboi69]

sir pls complete deep learning playlist plssss

[@superintelligence-Supremacy]

complete deep learning playlist plssss

[@ubaidurrehman5566]

Kindly sir upload deep learning complete road map video please. As you upload complete ( almost 2 hours ) machine leaning roadmap... Kindly sir upload it.. If you search KZbin you can't find deep learning complete road map video... Please sir take notes it

[@ParthivShah]

Thank You Sir.

[@finaz_18]

Sir wonderful explanation

[@ChandrakalaKurubaTechieStuffs]

much needed video..Thank you soo much...cud you do videos on optimization techniques like Whale, Ant Colony etc

[@alokmishra5367]

Excellent letcure ❤

[@rose9466]

Please complete the deep learning playlist.

[@meenatyagi9740]

Sir you calculated log odd w.r.t 1 ,postive class.But if someone use it for negative class like log(3/5) ,will result get affected?

[@kratikaagarwal7675]

Sir I have a confusion in this video , when you were calculating leaf_entry 2 , then for node 2 and node 3 the values were 0.188 and 0.055 respectively and for residual values were 0.33 , -0.10 and 0.1080 respectively , here the values are different , so how can we put them in that node?

[@hossain9410]

what to do for multiclass classification problems??

[@Sandeep_Kotha]

Hi Sir, I noticed that error is calculated as targe_value is subtratced with probability value . One column is label and other column is probaility , how we can subtract those two different quanties? error = target_lable - predicted lable right?

[@Tusharchitrakar]

Because target label is essentially a probability of the major class (1 means 100% probability of getting class 1 and 0 means 0% probability of getting class 1)

[@muraliendla7959]

amazing stufff highly recommended for ml👋👋👋

[@bloom6874]

can any one answer that how many minimum and maximum models can we take in Gradient Boosting model? is it 8 to 32? for better performance?

[@rockykumarverma980]

Thank you so much sir 🙏🙏🙏

[@smrutirekhaswain4408]

why we are not using GradientBoostingClassifier()? can any one answer?

[@gouthamsamrat6365]

Superb lecture

[@shubhampatidar7850]

Sir, is there any plan to start the 2nd batch of this course "data science"

[@superintelligence-Supremacy]

thank you sir please upload more

[@1LalitYadav]

Sir please make video on XgBosst also

[@superintelligence-Supremacy]

i want to be the father of Artificial general intelligence complete deep learning playlist for me and other who is self-learner

[@satyamgupta4808]

very very thankful to you

[@RamandeepSingh_04]

Sir but how will this concept work with multi class problem? Please tell sir

[@mohammednadhim1918]

Same doubt

[@1111Shahad]

Thanks Nitish.

[@rohitrannavre9382]

Still waiting for new video content in your deep learning series. Hope you will take care of it.

[@lug__aman]

Sir agar apke course mai month k liye abh payment kru toh video ka access kb tk milega ?

[@aiml66_bangerashashankchan81]

1 month

[@async341]

Gate ke liye kuch special h?

[@Ritz7sh]

Sir, notes please, give us a drive link

[@vinitkulkarni4197]

Sir non engineering can learn data science ai all for technology relted for ther use for business improve and business growth example small fast food business

[@KartikKumar-h5r9w]

no

[@sourabhiitian]

anyone confused with how leaf entry column values came use this function df['leaf entry']=tree_model.apply(X) where df is the database tree_model is the DT classifier model X=df['features']

[@rubayetalam8759]

is this video part of your 100 days of ML playlist?

[@mohdfarman3470]

Thank you sir❤

[@casepoint10]

Thanks Sir ❤

[@yashkumaryashkumar3026]

Sir can i join this paid season right now ?

[@parvejsheikh4364]

Sir, please complete deep learning playlist,❤❤❤❤

[@parvejsheikh4364]

😅💯💯

[@MECHINELEARNINGAI]

Sir Please complete the MLOps playlist Sir Please Sir Please Sir Please

[@maazshaikh9503]

Sir aap Genrative Ai and LLM pe videos banao

[@mallemoinagurudarpanyadav4937]

Thankyou sir

[@kartikverma6988]

🎉🎉🎉

[@thatsfantastic313]

Sir isko 100days wali playlist me daldo

[@not_amanullah]

already explained 😢

[@gazalla3656]

Sir can you please send me your email address as I am working on classification.

[@superintelligence-Supremacy]

sir pls complete deep learning playlist plssss