I would like to add one more challenge for Machine Learning which is 'Technical Debt'. It is a famous term that coins negative environmental issues due to Machine Learning, model training, and so on. Tons of people and organizations are training the ML model by processing days and nights this can negatively affect the environment which is proven in a research paper called 'Technical Debt'. Other than that, I have watched your many videos and They all are super amazing. I found it very helpful even after graduating from the Artificial Intelligence program.
Im learning from Ineuron ,de taught well and learnt the basic from dem but after seeing ur video which aint dat lengthy nd to d point, its helping me to retain some of the concept that I forgot over a period of time..Tnx for dis playlist..Im watching it straight nd will try to finish it within 4-5 days..After dat will start watching ur DeepLearning playlist
12:29 off topic but location does play a role in fittness , there is a reason why europens inheriting viking gene are fitter or arab from desert are fitter or people from harayana are fitter, Harsh climate work condition = fitter people
In the comment I can see many of you want a Note for these lectures so, for the notes follow this book Hands On Machine Learning with Scikit Learn and TensorFlow By O'Reilly
wanted to ask... aren't the examples of sampling bias and noise opposite of what they should have been? ie. Since noise is due to chance and not issues in the process of sampling, shouldn't the 2nd one be noise because we chose diffferent countries, but all were indians due to chance. This error will go away eventually as sample size increases. Whereas the first one is bias since it does not matter how much data we gather, the issue will persist as something is wrong with our sampling process, ie not sampling from many countries.
You can't get data Directly that You need that's why sir said Data is limited . I know In the internet Data present in Massive ammount as sir Discussed 1st points Data collection that is Quite Difficult For Data Collection You need More Cost because Everytime you don't get data freely ( You need API and Webscraping ) some Internet website or Tools are Premium for getting or scrapping the data Don't Focus on My English ( I'm little Weak in Language)
I guess apne sampling noise and bias ulta bata diya... Agr sirf india me question krte ho saare teams k baare me ki kon jetega toh wo bias hoga lekin baaki countries me bhi question krne me garbar horhi h toh because india wale hr jagah h is an example of noise
It's very difficult to wait for 100 days, this videos are so addictive that should be 100 hours of ML.
seriously
Sir, u r the best 🌟🌟 .. I just wanted to thank u so much for everything you have done for all of us..💝✨
I would like to add one more challenge for Machine Learning which is 'Technical Debt'. It is a famous term that coins negative environmental issues due to Machine Learning, model training, and so on. Tons of people and organizations are training the ML model by processing days and nights this can negatively affect the environment which is proven in a research paper called 'Technical Debt'.
Other than that, I have watched your many videos and They all are super amazing. I found it very helpful even after graduating from the Artificial Intelligence program.
Can you explain what could be the issue if I train continuosly for 5-6 months non stop like u said?😅😅
@@saiprem5380 carbon footprint increase
ap jaisay teacher bohot hi kaam hotay hain .bohot hi acha samja tay ho
Sir, You are Legend on ML.
I'm learning ML on best way from you.
& that Koili 🐦 sound are too peaceful ☺✨ 😍😍😊.
How are you doing now? Were you satisfied with the course?
Sir....
Pehele kyon nahi mile aap....
Ab jake kuch sahi me padh raha hun sir, our chijen dhyan me aa rahi hain.....🤘
Thank you so much...😌🙏
No other course can beat you in knowledge and explaination.
Bhai God Level hai lectures
revising my concepts now. Thank you
this channel is hell underrated.
great video,great knowledge and obviously a great teacher
sir you are very honest in your teaching, thank you a lot for providing this very useful video playlist for free.
I am very excited watch this vedio in 2024 , thanks sir 100000000000 time , i request ki or vi bahut sari vedio ap bano or kuch project se releted vi
May you be abundantly blessed with happiness in your life for graciously dedicating your precious time to us.
With heartfelt regards from Pakistan🥰🥰🥰.
Im learning from Ineuron ,de taught well and learnt the basic from dem but after seeing ur video which aint dat lengthy nd to d point, its helping me to retain some of the concept that I forgot over a period of time..Tnx for dis playlist..Im watching it straight nd will try to finish it within 4-5 days..After dat will start watching ur DeepLearning playlist
Same here.
+1
Whenever I come to your channel I always learn something NEW
Honestly You explain very well.
bro you are seriously the most underrated youtuber
Learning in 2024...
Same bhaii❤❤
Mee too bro!!
@@krishanubanerjee5806same bhai 🫂
same
Me too after realizing the value 😢
Great explaination, thanks for sharing.
Sir also upload video on how to create dataset. What precautions we should take while creating it.
its 2024 and im working as MLOps ... planing to be a Data Scientist and have some research background :)
12:29 off topic but location does play a role in fittness , there is a reason why europens inheriting viking gene are fitter or arab from desert are fitter or people from harayana are fitter, Harsh climate work condition = fitter people
Sir thank you so much for this ML series
this channel is such a goldmine
i thought krish naik and campus x are same guy🤣
Why?
But both are doing very good things for us. Because there are many online courses they are just looting by name of AI and Data Science
muze bhi lagatha, dono bhi mast sikhate hai
He is co founder of Campus X
Thank you so much sir
great sir , thanks for the gems
Explained very nicely
Will u cover deployement a model and buidling end to end project ?
Yes.
Programming GOD , simply underrated genius.
A Great Teacher
Course Started : ML
Lecture-01: 14/08/2024
Lecture-02: 14/08/2024
Lecture-03: 14/08/2024
Lecture-04: 14/08/2024
Lecture-05: 14/08/2024
Lecture-06: 15/08/2024
Lecture-07: 15/08/2024
@fit_tubes_365 hey bro did you complete this course and is this course is complete course.
In the comment I can see many of you want a Note for these lectures so, for the notes follow this book
Hands On Machine Learning with Scikit Learn and TensorFlow By O'Reilly
wanted to ask... aren't the examples of sampling bias and noise opposite of what they should have been? ie. Since noise is due to chance and not issues in the process of sampling, shouldn't the 2nd one be noise because we chose diffferent countries, but all were indians due to chance. This error will go away eventually as sample size increases. Whereas the first one is bias since it does not matter how much data we gather, the issue will persist as something is wrong with our sampling process, ie not sampling from many countries.
you are gem dude.
Thanks so much,
This is so helpful
Amazing Explanation.
How can I get access to your notes..? May be one note which you are using fro explaining 🙂
Gautam Gambhir jaisa admi hoga tw....data representetive hona hi he
Thanks Sir
Can you suggest some research topic in details from machine learning
Amazing sir
Dear sir kindly share the article link you were talking about cost of AI
@CampusX can you please share the notes of the 100 days ML course,
Sir how to get notes...
nicely explained
can you please share the one-note link sir for our reference?
UNDERSTOOD
day 7 done !!
10 july 2024
8:03 PM
Can you please share the slides for every video? it would be best.
Thanks.
amazing
Sir I think you followed "Hands on Machine learning"
thankyou
Sie please share the notes of the all videos 😊😊😊😊
Can You please upload the link of the notes. Thank a lot for such a helpful playlist.
NOTES PLEASE Sir!
finished watching
Hi @Sandipan ,How are you making Notes!!!
sir please provide the notes though
completed day 7 on 22-12-2024
day1:date:9/1/2024
day 3 - video 7
hey bro is this playlist is complete and good for beginers.
awesome
Can you provide notes of all class
#day1
but sir you said, ' data is endless there is lot of data in the world ' and now you are saying limited data. Please explain this
You can't get data Directly that You need that's why sir said Data is limited . I know In the internet Data present in Massive ammount as sir Discussed 1st points Data collection that is Quite Difficult For Data Collection You need More Cost because Everytime you don't get data freely ( You need API and Webscraping ) some Internet website or Tools are Premium for getting or scrapping the data
Don't Focus on My English ( I'm little Weak in Language)
master blaster ,,,
Sir notes please
Day 7 - 27/04/24
Soft tooo
Sir please make a playlist on web scraping..!
Day - 3
Lecture - 06 (18/09/24)
bro is this playlist is complete and good for beginers and also relevent in 2024.
@@ytshorts2788 Sorry I'm not sure , I stopped in the middle due to personal reasons (College Placement Work)
@22:04
sir upload next videos
I guess apne sampling noise and bias ulta bata diya... Agr sirf india me question krte ho saare teams k baare me ki kon jetega toh wo bias hoga lekin baaki countries me bhi question krne me garbar horhi h toh because india wale hr jagah h is an example of noise
Can you take in English
love from Pakistan bro
Day 7 ,,,, 2-11-2024
Day 7; 19.04.2023
Bro are you making notes ?
yes
@@ashitoshmalwade7066
11:40
6:00
GG
Over fitting: Ladies think all boys are same
Your example of overfitring isnt good,
Thats the example of bias, you are biased towards gurgaon city
learning in 2k25
Same bro
who''s watching this video after T20 won ?🤭
day4 23/01/2025
Sir, You are Legend on ML.
I'm learning ML on best way from you.
& that Koili 🐦 sound are too peaceful ☺✨ 😍😍😊.
Can you take in English