I am really surprised why you are getting so less views…you are making complex things so simple …you are making really quality content please keep making videos may be not today but in one day people realise your work …waiting for it
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!
Bro, you have done a very good job...I wasted much time on other videos but after seeing yours I completely understand. Thank you...Please carry on making such brilliant tutorial videos.
Brother! I am from Bangladesh. I am really surprised to watch your explanation. Your explanation is totally awesome. Any kind of learner can be easily understood your lecture. Keep up your good work bro.
thank you so much bhai because of you i and my team able to deliver end to end project in our internship project. we followed couple of videos based on our difficulty which we were facing it but after referring your videos we we able to solve the problem.
Your content needs to go out to everybody who thinks Machine learning theory is ! What a wonderful explanation. . Saw this video 4 times as it took some time to grasp this but language which used is simple ,clear and content is informative !
Very well explained. I also want to ask what if the stacking model gives lower accuracy than the base model (like RFC, CBC). How can we justify this without changing the base model combination? Thanks in advance.
in the sense stacking works somewhat similar to boosting for ex you train one model and based on the trained model's output u train one more model to get the output
Hi, Does anyone know why do we train the base models again after getting the meta model? Whats the use of it? Arent the predictions based on the output of meta model?
i guess it is because, when predicting if we take test data, which has 2 features cgpa and iq, we first need to convert this into the features that our meta model knows (basically 3 features) so we send these 2 features to the 3 base models(which were trained on the 800 dataset after getting the meta model) which gives us 3 features (their predictions) which we can then feed into our meta model. he didnt explain why we need to train the base models again, but i think this is the reason
Please correct me if I am wrong, in multi layer stacking - you are training 2nd_layer's model based on layer_1's predictions , and you said now we will predict layer 2's model using dt3 , please clear this doubt By the way huge fan , thanks for simple and straight explainations
Nitish Sir, Thanks a lot fort the amazing content! I think you should definitely start an English version of Campusx for a better reach. You'll definitely have a better reach. BTW we both have the same name with a different spelling. Thanks again! :)
Hello sir, if we use hold out method in stacking, i am using it in medical dataset, training accuracy -80 % and testing accuracy - 85 %, but training and testing sensitivity -100 % , so does this mean my model is over fitting?
You are doing great sir. I am following entire playlist. I have seen a dream 11 team predictor system but not able to understand proper logic after seeing the codes. Please explain the project as i like the idea of the project
Sir i want to sorry you because i disrespected your content one day when i was new to your channel because voice quality was not good and i didn't understand the concept but when i progressed then i came to know that how foolish i was i found a most comprehensive machine learning course on whole RUclips ❤❤❤❤❤❤
I am really surprised why you are getting so less views…you are making complex things so simple …you are making really quality content please keep making videos may be not today but in one day people realise your work …waiting for it
yeah I felt the same many times
achhi baat h ye toh jitne kam log dekhenge utna accha rhega.
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!
Bro, you have done a very good job...I wasted much time on other videos but after seeing yours I completely understand. Thank you...Please carry on making such brilliant tutorial videos.
Thank You sir I am following you since last few days, and everyday I wait for your videos
Brother! I am from Bangladesh. I am really surprised to watch your explanation. Your explanation is totally awesome. Any kind of learner can be easily understood your lecture.
Keep up your good work bro.
thank you so much bhai
because of you i and my team able to deliver end to end project in our internship project. we followed couple of videos based on our difficulty which we were facing it but after referring your videos we we able to solve the problem.
Wow. What an explanation I have seen while going back again and again.
Amazing content right here 👍 You made the concepts a real ease to comprehend. Kudos and best wishes👍
Excellent content - thanks for sharing and explaining in such lucid way - even the complex math sometimes.
Brother Really your teaching is on another level I swear! kya Krish Nayak hato bakwaas Ye hai asli guru ,
bhai bahut shi aadmi ho... life me kafi aage jaoge. Nice teaching.
amazing content!!! could not find such detailed video on youtube..👍👍
Sir can you please continue the gradient boosting series
bahut hi sandar video sir ji
ur channel is lit
Your content needs to go out to everybody who thinks Machine learning theory is ! What a wonderful explanation. . Saw this video 4 times as it took some time to grasp this but language which used is simple ,clear and content is informative !
Where can we read about all these models as explained by you? Can you please refer to the relevant textbook or literature?
genuinely the most confusing video in this playlist because of the sheer onslaught of info that does not stop overloading your brain
If u found any other resources for stacking and blending, please help, i am not understanding it
One word superb 👏
Very well explained. I also want to ask what if the stacking model gives lower accuracy than the base model (like RFC, CBC). How can we justify this without changing the base model combination? Thanks in advance.
where is day 68 ToT
Channel is so underrated that i found it very late
can you please share the next lectures also?
Superbb explanation 👌👌
anyways, your explanation is awesome.loved it
Thank You Sir.
in the sense stacking works somewhat similar to boosting for ex you train one model and based on the trained model's output u train one more model to get the output
Very well explained, thank you
Hi, Does anyone know why do we train the base models again after getting the meta model? Whats the use of it? Arent the predictions based on the output of meta model?
i guess it is because, when predicting if we take test data, which has 2 features cgpa and iq, we first need to convert this into the features that our meta model knows (basically 3 features) so we send these 2 features to the 3 base models(which were trained on the 800 dataset after getting the meta model) which gives us 3 features (their predictions) which we can then feed into our meta model. he didnt explain why we need to train the base models again, but i think this is the reason
Please correct me if I am wrong, in multi layer stacking - you are training 2nd_layer's model based on layer_1's predictions , and you said now we will predict layer 2's model using dt3 , please clear this doubt
By the way huge fan , thanks for simple and straight explainations
Yes layer2 will train on layer1 pred on DT2 then layer2 pred on DT3 will be input to meta model or next layer.
decent explanation
What is your Kaggle profile? I mean what is your Rank on it?
Nitish Sir, Thanks a lot fort the amazing content! I think you should definitely start an English version of Campusx for a better reach. You'll definitely have a better reach. BTW we both have the same name with a different spelling. Thanks again! :)
@22:30 "every base model trained 3 times" K=4 how?
Kya machine learning idhr khtm hota h???
sir thank you so much ... abhi to 35th video pe hu par jald hi yeh video pe aa jaunga
while implementing stacking myself iam getting 70 % but though built in iam getting 80% why?
Hello sir, if we use hold out method in stacking, i am using it in medical dataset, training accuracy -80 % and testing accuracy - 85 %, but training and testing sensitivity -100 % , so does this mean my model is over fitting?
Sir you are grt, unsupervised ke bhi Sare algo ke video bna dijiye plz
can i get your handwritten notes
You are doing great sir. I am following entire playlist. I have seen a dream 11 team predictor system but not able to understand proper logic after seeing the codes. Please explain the project as i like the idea of the project
Thank you 3000
Brilliant
Thank you sir
Very Good Video!!!
Thanks
excellent
finished watching
I won't lie you are someone who can teach ML to 10 years old boy 😅
Sir i want to sorry you because i disrespected your content one day when i was new to your channel because voice quality was not good and i didn't understand the concept but when i progressed then i came to know that how foolish i was i found a most comprehensive machine learning course on whole RUclips ❤❤❤❤❤❤
is this guy speaking in english?
this video is little bit confusing...
Speak ENGLISH!
Hello Nitish, I just want to inform you that I have drop you a message on your email. I will appreciate your urgent response. Thanks prof.
Replied
can you share me his email please