Ensembling, Blending & Stacking

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  • Опубліковано 23 гру 2024

КОМЕНТАРІ • 79

  • @abhishekkrthakur
    @abhishekkrthakur  4 роки тому +17

    If you want more stable coefficients when finding the best weights for blending, please use a different initialization.

    • @its_me7363
      @its_me7363 4 роки тому +1

      very informative video...pls make videos on image annotation from scratch

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +3

      like annotating images manually?

    • @its_me7363
      @its_me7363 4 роки тому +1

      @@abhishekkrthakur whatever people in kaggle competition use.

    • @its_me7363
      @its_me7363 4 роки тому

      I DM'ed you in twitter regarding this.

    • @Pratapsingh-ng7pr
      @Pratapsingh-ng7pr 3 роки тому

      sorry to bother Abhishek, can u please share the link from where we can get the source codes u are using . specially the optimal_weights.py file .

  • @MrAnandml
    @MrAnandml 4 роки тому +15

    Glad ...to see this sort of contents ...Believe it or not these channel is going to be the best in ML,DL and AI ..
    Some thing equivalent to an University ...

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +2

      Thank you 🙏

    • @scharlesworth93
      @scharlesworth93 2 роки тому

      There is a lot of garbage on youTube but this dude you can tell he's a professional.

  • @aditya_01
    @aditya_01 3 роки тому +1

    Really all your contents are awesome,your books ,videos all r much more than an university .Please keep sharing

  • @mnoossum8344
    @mnoossum8344 4 роки тому +16

    Also please make a video on feature selection on tabular data....
    Please abhishek sir🙏🙏🙏🙏🙏

  • @nirmaltiwari6636
    @nirmaltiwari6636 4 роки тому +5

    I have bought and gone through your book. It is just excellent...I would say it is ultimate... Thanks...

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому

      Glad you like it. Please do consider writing a review on Amazon too :)

  • @samtasticcreations
    @samtasticcreations 2 роки тому

    Wow, what I needed, thanks for the helpful tutorial

  • @mishrasidharth
    @mishrasidharth 3 роки тому

    absolutely best timing on your videos thanks !!!

  • @mrigankanath7337
    @mrigankanath7337 4 роки тому +7

    The next video on reinforcement learning? you can use the Halite competition in kaggle to make us understand

  • @allieubisse470
    @allieubisse470 4 роки тому +2

    You're a true Grandmaster.😅😅 it's not easy to skip your lessons

  • @aboba_amogusvna
    @aboba_amogusvna 2 роки тому

    Man you are on another level..

  • @razintailor
    @razintailor 4 роки тому +1

    I pre-booked the Kindle version India. The book is so lucid to understand. I really appreciate the efforts in the write-up and the knowledge that's been provided in the book. Honestly learned alot.

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +1

      Thank you! Please do consider writing a review on Amazon too :)

    • @razintailor
      @razintailor 4 роки тому

      @@abhishekkrthakur I will indeed.

  • @venkataramanamaram4041
    @venkataramanamaram4041 4 роки тому

    I wonder why two dislikes, you guy's can comment what is missing so that Abhishek Thakur will respond to you and we all can benifit from this. My suggestion in future if you are dislike please comment why and what is missing from Abhishek. Look below he is patiantly answering most of the comments to his best. Personally I learned a lot but need more hands-on to get this skill. A special thanks Abhishek Thakur for serving in this manner. You are my motivation to deliver content for free.

  • @vinaytiwari5914
    @vinaytiwari5914 4 роки тому +1

    Amazing video Abhishek. You keep emphasizing on the importance of cross validation setup so how do u go decide the correct cross validation setup for a given problem?

  • @rajsinghrajpoot8945
    @rajsinghrajpoot8945 4 роки тому +5

    Please make video on GAN

  • @floopybits8037
    @floopybits8037 2 роки тому

    This is one of the most comprehensive tutorial on blending and stacking very amazing work from your side
    I have a query if i have a multi class targets with probabilities how will i compare the accuracy ??

  • @asiftandel8750
    @asiftandel8750 3 роки тому

    Great video

  • @amanpatkar7009
    @amanpatkar7009 3 роки тому

    i bought your book from pothi. Looking more books from your end.

  • @vivekchowdhury4225
    @vivekchowdhury4225 3 роки тому

    That was a fantastic video GrandMaster! 😁👍

  • @AyushGupta-kp9xf
    @AyushGupta-kp9xf 4 роки тому

    much-awaited video ! thank you so much sir

  • @darkjediist
    @darkjediist 4 роки тому +1

    You are doing linear blending; however, your optimized weights are not adding up to 1. Do you think this is a problem?

  • @Pratapsingh-ng7pr
    @Pratapsingh-ng7pr 3 роки тому

    While creating new features using existing features, which features to consider (features with low correlation with target) or can I use features which have high correlation with target to create new features. Or both ?

  • @alexdelaiglesia1926
    @alexdelaiglesia1926 3 роки тому

    Very good tutorial! What about ensembling when we have time series data?

  • @jackbauer322
    @jackbauer322 3 роки тому

    why are you creating a fold column ?

  • @sunilkumargupta7980
    @sunilkumargupta7980 3 роки тому

    Please creat a video on feature selection and extraction techniques..

  • @ofdomejean
    @ofdomejean 4 роки тому

    Just amazing Sir, you helped me to clear lost of concepts.

  • @shubhamarora2219
    @shubhamarora2219 4 роки тому

    Awesome work !!! ❤️
    Thankew so much sir 🙏
    Earlier i had question in my mind how to find the optimal model cofficients but today i got the answer to that.
    Also good to to know about rank averaging 🙌

  • @zzzubin
    @zzzubin 3 роки тому

    How do you do blending with time series split ? total valid set size < total train set size in this case and L1 will be the time series split folds. Should I then use only the valid set OOF preds to do L2 (probably without regards to time anymore and treat it as regular K-fold here onwards) ? Is this the correct approach ?

  • @asogwakenneth1621
    @asogwakenneth1621 4 роки тому

    Thank you for this sir!
    I can't wait to learn more from you

  • @ambarishkapil8004
    @ambarishkapil8004 4 роки тому

    Hi Abhishek, thanks for the great content you are providing. I wanted to hear your opinion on AutoML, how do you think it will evolve and how will it change things.

  • @viveksrinivasan5809
    @viveksrinivasan5809 2 роки тому

    Hi Abhishek. I know that I'm late but can I use optuna to find optimate weights for ensembling? After all, it's just a function that needs to be optimized right? Won't optuna work well?

    • @abhishekkrthakur
      @abhishekkrthakur  2 роки тому

      yes you can. im not sure i made a video about it but you can read it with code in my book: bit.ly/approachingml. its free

  • @manabendrarout
    @manabendrarout 3 роки тому

    Really cool video as always Abhishek!
    I actually meant to ask you how did you setup this code server that you are working on?
    I recently built a workstation PC for data science stuff, but I do not want be "immobile" because it's a PC. How can I replicate this setup which you use (without using Remote Desktop)?
    Any resources or links would be super helpful. Thanks :)

  • @sajalhsn13
    @sajalhsn13 2 роки тому

    Why can't I like this video more than once? It's unfair!!

  • @Karenshow
    @Karenshow 2 роки тому

    Ensembling time series models into one.

  • @praveengovi
    @praveengovi 4 роки тому

    Beautiful video Abhishek , This video is more insightful and gave clear roadmap in blending and stacking; How about using mean , median value to use instead of averaging method can we use those can we use it in weighted averaging

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +1

      thanks! and yeap you can try many variations. even gm, hm, etc. I didnt go in details there and left it as something to explore ;)

    • @praveengovi
      @praveengovi 4 роки тому

      @@abhishekkrthakur Noted Thanks 🙏 Sir

  • @vineethrajb8814
    @vineethrajb8814 4 роки тому

    Can you do a video for the final optimization of multi targets?

    • @vineethrajb8814
      @vineethrajb8814 4 роки тому

      Got it thanks

    • @vineethrajb8814
      @vineethrajb8814 4 роки тому

      got multiple values for argument 'X' Got this error possible solutions to solve this?

  • @shashankpulijala3378
    @shashankpulijala3378 4 роки тому

    Great!!

  • @GairolaAbhijit1991
    @GairolaAbhijit1991 4 роки тому

    Hey Abhishek ! Is it a standard practice to use the ID column in the dataset for training the model? I understand that keeping in the ID column might convey some added information to the model in competitions, but is it an advisable practice while training models for prod?

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +1

      No No. Never keep the id column to train the model. Did I do that?

    • @GairolaAbhijit1991
      @GairolaAbhijit1991 4 роки тому

      @@abhishekkrthakur You don't drop the id column from the training set for either of the three L1 level models, and ID column is again used in the blending.py file to merge the datasets together.

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +1

      @@GairolaAbhijit1991 you made me look at the code again. haha :D yes. i do keep ID column. its a way to track the data points for all the models. but do I use the ID column to train the models? NO! Look carefully, I have always defined which columns to use for training the models :)

  • @oostopitre
    @oostopitre 4 роки тому

    Thank you for the video. As usual amazing high quality content! Is there a difference between when the words 'blending' and 'stacking' are used? Are they just synonymous used? I tried to read up on it but could not find a clear distinction.

    • @abhishekkrthakur
      @abhishekkrthakur  4 роки тому +2

      Many people have many different definitions. here is mine: stacking is when you use a model to combine base models and blending is when you combine models just by weighted average. Although weighted average can also be thought of as a model. Some also say stacking is kfold and blending is on a holdout set. :)

  • @data_quest_studio4944
    @data_quest_studio4944 4 роки тому

    This masterpiece will surely help everyone ! Thank you Abhishek Bbhaiiay ! There is one request , can u do a small video in Hindi ! Just for fun :)))

  • @evgeniachubata4119
    @evgeniachubata4119 4 роки тому

    Great video! Thanks! Learned a lot. I will assume that the code from this video can be found in your book. Is this correct?

  • @hasanmoni3928
    @hasanmoni3928 4 роки тому

    How can I get your Machine Learning book in Bangladesh?

  • @ShortVine
    @ShortVine 4 роки тому

    thank you for this vid.

  • @andreacosta9576
    @andreacosta9576 Рік тому

    I cannot see where the target is dropped?

    • @abhishekkrthakur
      @abhishekkrthakur  Рік тому

      everywhere. if it's not dropped, its not used. if it's used, its used in cross validated manner to generate target encoded variables.

  • @bondarchukb
    @bondarchukb 4 роки тому

    very cool

  • @Leo-xd9et
    @Leo-xd9et 3 роки тому

    The video is long, but really easy to follow!

  • @abhijeetnarharshettiwar6175
    @abhijeetnarharshettiwar6175 4 роки тому

    xtrain column names

  • @Phateau
    @Phateau 4 роки тому

    Dropping bombshells here!

  • @rajanlagah4529
    @rajanlagah4529 4 роки тому

    Long one. But worth it xD..