Imbalanced Data in Machine Learning | Undersampling | Oversampling | SMOTE

[@campusx-official]

I had to reupload this video because I forgot to include the part on ensemble techniques due to an editing error in the previous upload. Check timestamps.

[@Ashishkumar-id1nn]

Sir, please make a video on the difference between encoding and embedding

[@mohitjoshi8984]

Sir please make a video on AB testing

[@AMANRAJ-dt8gu]

I am writing to request your assistance in creating videos that delve into metaheuristic approaches, such as genetic algorithms, ant colony optimization, and others. It has come to my attention that there is a noticeable scarcity of resources covering these topics on platforms like KZbin.

[@sagarbp-2854]

Sir make video about AB testing

[@adityamartand9927]

Thanks sir

[@advaitdanade7538]

Thank you sir for the best series on KZbin, I just completed it in 2 months by watching 4 hr daily at 1.5x speed

[@momscookbook2222]

Which series

[@advaitdanade7538]

@@momscookbook2222 campusx ml playlist

[@hasanrants]

Series officially completed on 10th October 2024. Thank you Sir Nitish for the valuable content. It was an honor to study from you.

[@SMBEATS-cb7sh]

Awesome explaining!!! I'm not just talking about one video-the entire ML playlist is AWESOME! After consistently dedicating around 5 months to this playlist, I now feel confident in my ML skills. A big thanks to @Nitish Singh for this incredible journey!

[@ParvezGKhan]

Excellent explanation. Thanks a lot Sir. I was having a very imbalanced data set. For diabetic patients 300000 samples of non-diabetic patients and 56000 diabetic patients. Due to this prediction was very bad, and hence i was looking for these techniques.

[@shumailmalik5948]

I am Shumail Malik, a PhD student at Hanyang University, South Korea. I have seen you transition from a young person to an older one over these 100 days of Machine Learning. Without a doubt, you have done great work for the public! Your teaching style and accent are truly impressive, and your simplicity in personality is very attractive. Thank you very much, Sir.

[@ArpitRawat-ew7ni]

Hey what's your researching in ? How is life there?

[@shumailmalik5948]

@@ArpitRawat-ew7ni biomedical engineer. Life is perfect. In every prospective.

[@ArpitRawat-ew7ni]

@@shumailmalik5948 oh great Is ml in medical also?

[@devamsingh9252]

Thankyou sir, I started the playlist on 25/08/24 and completed today ( 16/09/24 ). I learned so many things. I spent much time learning the ML from various sources like Codebasics, Krish Naik, Coursera but you provided the depth knowledge of algorithms with beautiful easiness❤.

[@ansh-t8e]

Thanks sir for this beautiful playlist. Never have i ever thought i would be able to understand all concepts of ml so easily. i am really grateful to you. i just completed this playlist after grinding for around 2 months. I have been going with some problems in my life that i am fighting but i will come out stronger now that I have completed this, soon I will start the DL playlist too and complete it too. Thank you for everthing sir.

[@manikarnikatiwari199]

THANK you so much Nitish 😊u are the best in everything.🎉 Thanks for being my teacher 😊🙏

[@Himu-c5l]

Thanks sir for the best Ml playlists on KZbin . Coming from a non techn background you make it really easy to understand all things

[@shripaddeshpande5766]

Another fantastic video by Nitish! Wonderful!!!

[@AkriteePathak]

I understood everything sir Thank you so much You are the best

[@divyakarlapudi]

Thankyou so much for this video, very helpful sir 🤌

[@068sushant8]

Finally i completed this playlist🤩🤩

[@rockykumarverma980]

Thank you so much sir🙏🙏🙏

[@Ritz7sh]

Sir, please share the notes of your latest videos like Optuna, imbalanced class and xgboost etc in the video description. It would be a great help for us.

[@hitanshramtani9076]

Hi Sir as i have finished you 100 days ml playlist what can be our next step, please guide, Thank You Sir for your great playlist and Great Explanation.

[@vinayakvijay108]

Awesome Content

[@ShubhamAware-yl5wd]

lets suppose in my data % of good customers is 95 and % bad customers is 5. the data is highly imbalance and I want to build a classification model for that I have to balance the data, then up to what % should I oversample bad customers? how can I identify it what % is optimal?

[@ParthivShah]

Thank You Sir.

[@uditbhandari5791]

Sir, when will you start a new batch for DSMP?

[@momscookbook2222]

Thanks🙏

[@AMANRAJ-dt8gu]

I am writing to request your assistance in creating videos that delve into metaheuristic approaches, such as genetic algorithms, ant colony optimization, and others. It has come to my attention that there is a noticeable scarcity of resources covering these topics on platforms like KZbin.

[@wamiqmushtaq2825]

Sir pls do a session on cross validation.... There's no sperate video on cross validation in the ml playlist

[@balrajprajesh6473]

Thank you very much sir

[@sameere1223]

Sir feature selection techniques are remaining topics

[@shlok7580]

i had this in an interview recently and i fkd up a bit :( They gave me a dataset and were expecting how to handle such type of data and make it soo that the predictions that we make are reliable

[@himanshurathod4086]

please continue your llm transformers series.and also please upload nlp ner and topic modeling

[@hossain9410]

my test dataset is imbalanced . can i apply oversampling on test dataset???

[@tusharshukla9361]

Nitishi Sir please update your Machine Learning Roadmap and add links of your new videos (We want more and more videos of yours)

[@nsbipritam9682]

very helpful video

[@chandrimapramanick1111]

Sir, I truly admire your work and love all of your videos, learning so much from them. Thank you!!! I have one question: at the end of the video you said that in spam filtering false positive is the critical one but if one msg is spam and classified as not spam(false negative) that will be the critical case isn't it? false negatives are generally considered to be more dangerous in this case because they can expose the recipient to potential harm.

[@RajatTomar-r7i]

I think false positive is more critical because it may send your important mail in spam which is more harmful rather than showing some spam mails as important mail.

[@souvik5560]

Nitish :- At 7:00 It will be "Testing data" for determining the accuracy. Am I correct ?

[@soumyaranjandas7394]

Dear Nitish sir, plz make video on how to fine tune our custom data using LLama llm.

[@muhammadikram375]

Sir please do some working on MLOps playlist

[@dineshpatel9877]

Hello sir please make video on ..PCA, tSNE, UMAP.

[@Sulehri226]

Thanks Sir

[@mukeshrajpurohit5593]

Hi Sir, Big Fan!! I was searching for class imbalance video and you have uploaded it on right time. I am training an ANN model for customer churn prediction where my dataset has class imbalance issues 96:4. I have used Upsampling, Downsampling, SMOTE, SMOTE-ENN, Class Weight but neither of them gave promising results and fail to predict well on minority class the recall value is very low. What should be done in such case where the model is not predicting well on minority class. I have also trained XGBoost classifier but that model also did not perform well.

[@parth.mandaliya]

Please make a new video on transformers 🙏

[@not_amanullah]

Thanks

[@bhushansonawane5915]

Hello sir, how can i connect with you ? Need urgent help please

[@haroonmalik2195]

Sir Also make video on multi label classification problem.

[@pujarameet9699]

Is this series complete or anything remaining sirm

[@anandshaw-ie3qk]

it's better

[@DharmendraKumar-DS]

Vijay Malya got hurt here😅

[@GhostRiley-g2s]

Playlist ke end tak aate aate aisa lag rha ki aap jawan se budhe ho gye.

[@dexterdev30]

42:46

[@not_amanullah]

🖤

[@mohitnemade5320]

Nitesh bhai aapka knowledge perfect hai but video itne long hote h ki chahke bhi pura nahi dekh pate.. please try to make video in short way🙏🤝👍

[@Mr_Sniper5]

Sab LLM ki bat Kar Rahe hai app Machine learning par ruke hai

[@abhinavkale4632]

Bhai LLM ke bhi videos cover kar Rahe hai nitesh sir. To us, these concepts are still gold and they are used everywhere.

[@Mr_Sniper5]

@@abhinavkale4632 bhai sir ke sare video mere laptop me hai all total video LLM ka history padhe hai abhi tak

[@omsaikommawar]

From an interviewer's perspective, an imbalanced dataset is a common topic in interviews. Focusing on simple topics can increase your chances of success in cracking the interview.

[@samarmohanty6109]

ML hogya kya apka

[@Mr_Sniper5]

@@samarmohanty6109 ha Mera generative Ai bhi ho gaya

[@Mr_Sniper5]

Sir app bahut peeche hai