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
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.
🌈✨ 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
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!
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 RUclips you can't find deep learning complete road map video... Please sir take notes it
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?
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']
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?
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)
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
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
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.
🌈✨ 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
Do you enroll in DSMP course.
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!
great session sir. really deep expalaination
Sir please continue the deep learning playlist you already have explained these topic previously
That last geometric visualization was just the best. Awesome Teaching Sir
You are a star ⭐
who taught us how to shine ✨
Happy teacher's day sir.. 🙏🙏💐💐
Wish you all the happiness in the world😊
sir please complete deep learning series
Thank you so much for this in-depth explanation.
Wonderful explanation as always ❤
sir pls complete deep learning playlist plssss
sir please complete your deep learning series please sir
He is going to do it very soon bro after he ends dsmp !
* Nitish Sir
complete deep learning playlist plssss
@16:00 if we do there are five 1 and total records =8, so why didn't we do probability = 5/8 which is also 0.62
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 RUclips you can't find deep learning complete road map video... Please sir take notes it
Sir wonderful explanation
much needed video..Thank you soo much...cud you do videos on optimization techniques like Whale, Ant Colony etc
Thank You Sir.
Please complete the deep learning playlist.
Excellent letcure ❤
Superb lecture
amazing stufff highly recommended for ml👋👋👋
Thank you so much sir 🙏🙏🙏
i want to be the father of Artificial general intelligence
complete deep learning playlist for me and other who is self-learner
thank you sir please upload more
Sir please make video on XgBosst also
Still waiting for new video content in your deep learning series. Hope you will take care of it.
Sir, is there any plan to start the 2nd batch of this course "data science"
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?
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?
Thanks Nitish.
what to do for multiclass classification problems??
very very thankful to you
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']
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?
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?
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)
why we are not using GradientBoostingClassifier()? can any one answer?
is this video part of your 100 days of ML playlist?
Thank you sir❤
Gate ke liye kuch special h?
Thanks Sir ❤
Sir, notes please, give us a drive link
Sir Please complete the MLOps playlist
Sir Please
Sir Please
Sir Please
Sir agar apke course mai month k liye abh payment kru toh video ka access kb tk milega ?
1 month
Sir can i join this paid season right now ?
Sir but how will this concept work with multi class problem?
Please tell sir
Same doubt
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
no
Sir aap Genrative Ai and LLM pe videos banao
Sir, please complete deep learning playlist,❤❤❤❤
😅💯💯
Sir isko 100days wali playlist me daldo
Thankyou sir
🎉🎉🎉
already explained 😢
Sir can you please send me your email address as I am working on classification.
sir pls complete deep learning playlist plssss