You are the best teacher I have ever seen for ML. I was eagerly looking for this level of conceptual understanding that you have provided in every video of the playlist.
Can you tell me under which part or specific topic in MAchine learning this (Evaluation and Cross-Validation ) comes under ? Or would you like to share the syllabus which do you follow ?
Can you tell me under which part or specific topic in MAchine learning this (Evaluation and Cross-Validation ) comes under ? Or would you like to share the syllabus which do you follow ?
Madam, in k-fold cross validation technique, what is the final estimate of the model parameters. Are they the average of all the rounds or the best round?
Training is to apply selected test cases on the learning algorithm in order to train them and validation is to test all the test cases and check its accuracy.
Professor Sarkar, you are an excellent teacher! Thank you for providing this tutorial. It has greatly increased my understanding of these concepts.
You are the best teacher I have ever seen for ML.
I was eagerly looking for this level of conceptual understanding that you have provided in every video of the playlist.
Best video to understand science and concept of ML. Thanks for sharing this video
Professor, Thank you very much for such a wonderful presentation. concepts you explain increased my understanding in ML
you are a good teacher as all indian teachers
Ki sundor kore bojhacchen apni...Pranam neben
You just saved me 2 hours of going thru Tom Mitchel's book. Thank you :')
Can you tell me under which part or specific topic in MAchine learning this (Evaluation and Cross-Validation
) comes under ? Or would you like to share the syllabus which do you follow ?
@@codermafia3441 cross-validation is a technique to tackle overfitting, evaluation is like an examination of a model
you are the beast thank you
it is better to tell an example to every concept
Oh nice video
Thanks.
Ur Lectures help me so much..thank u
Can you tell me under which part or specific topic in MAchine learning this (Evaluation and Cross-Validation
) comes under ? Or would you like to share the syllabus which do you follow ?
Great lecture
17:02 it should be underfitting instead of overfitting
Nope, overfitting is correct. Reduced data will lead to less generalization and, thus, will have high error rate on test data.
Madam, in k-fold cross validation technique, what is the final estimate of the model parameters. Are they the average of all the rounds or the best round?
check out "stat quest cross validation" on youtube..cheers!!
@@RENGcast Ok. Thanks.
Lecturer notes available?
Paagal ho gya mai to
What is the difference between Training and Validation?
Training is to apply selected test cases on the learning algorithm in order to train them and validation is to test all the test cases and check its accuracy.
Mahafarzi example
It’s better to get some real life example otherwise it becomes boring
sab farzi baaten koe practical real life problem ki example do ... dimagh pak gaya x aur y ki waja se.....
practical k liye --- ruclips.net/video/elojMnjn4kk/видео.html
Booooooooooooooooooooooooring
Bad teaching