Building models for recommendation system
Hi, I have a *1000x1000* euclidean* distance matrix.* The distance is calculated pairwise between each item i.e *distance between an ITEM with remaining ITEMS.* I would* like to know* the *next step after calculating the distance matrix.* Further, please* link some resources* so that I can get deep understanding because *as far as I have researched most of the websites provide examples with toy dataset which are pretty straight forward.* https://github.com/maxyodedara5/BE_Project/blob/master/test.ipynb is the link to the code CODE FOR READ ONLY PURPOSE. -- Regards
https://github.com/maxyodedara5/BE_Project/blob/master/final/test.ipynb new link for code On Tue, Feb 13, 2018 at 8:23 PM, prince gosavi <princegosavi12@gmail.com> wrote:
Hi, I have a *1000x1000* euclidean* distance matrix.* The distance is calculated pairwise between each item i.e *distance between an ITEM with remaining ITEMS.* I would* like to know* the *next step after calculating the distance matrix.* Further, please* link some resources* so that I can get deep understanding because
*as far as I have researched most of the websites provide examples with toy dataset which are pretty straight forward.* https://github.com/maxyodedara5/BE_Project/blob/master/test.ipynb is the link to the code
CODE FOR READ ONLY PURPOSE. -- Regards
-- Regards
Hello, If you after video/music recommendation set, I recommend you to check websites like kaggle and Analytics Vidya. However recently there was a competition organised by kaggle which is to do with Music recommendation and here is the link to the dataset. https://www.kaggle.com/c/kkbox-music-recommendation-challenge I think we are ought to keep the mailing list specific to scikit-learn. regards Manjunath On Tue, Feb 13, 2018 at 6:31 PM, prince gosavi <princegosavi12@gmail.com> wrote:
https://github.com/maxyodedara5/BE_Project/blob/master/final/test.ipynb new link for code
On Tue, Feb 13, 2018 at 8:23 PM, prince gosavi <princegosavi12@gmail.com> wrote:
Hi, I have a *1000x1000* euclidean* distance matrix.* The distance is calculated pairwise between each item i.e *distance between an ITEM with remaining ITEMS.* I would* like to know* the *next step after calculating the distance matrix.* Further, please* link some resources* so that I can get deep understanding because
*as far as I have researched most of the websites provide examples with toy dataset which are pretty straight forward.* https://github.com/maxyodedara5/BE_Project/blob/master/test.ipynb is the link to the code
CODE FOR READ ONLY PURPOSE. -- Regards
-- Regards
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Hi, Thanks for the response and Sorry for the trouble I will keep that in mind. Regards On Feb 14, 2018 16:40, "Manjunath Goudreddy" <manjunathgoudreddy@gmail.com> wrote:
Hello,
If you after video/music recommendation set, I recommend you to check websites like kaggle and Analytics Vidya. However recently there was a competition organised by kaggle which is to do with Music recommendation and here is the link to the dataset.
https://www.kaggle.com/c/kkbox-music-recommendation-challenge
I think we are ought to keep the mailing list specific to scikit-learn.
regards Manjunath
On Tue, Feb 13, 2018 at 6:31 PM, prince gosavi <princegosavi12@gmail.com> wrote:
https://github.com/maxyodedara5/BE_Project/blob/master/final/test.ipynb new link for code
On Tue, Feb 13, 2018 at 8:23 PM, prince gosavi <princegosavi12@gmail.com> wrote:
Hi, I have a *1000x1000* euclidean* distance matrix.* The distance is calculated pairwise between each item i.e *distance between an ITEM with remaining ITEMS.* I would* like to know* the *next step after calculating the distance matrix.* Further, please* link some resources* so that I can get deep understanding because
*as far as I have researched most of the websites provide examples with toy dataset which are pretty straight forward.* https://github.com/maxyodedara5/BE_Project/blob/master/test.ipynb is the link to the code
CODE FOR READ ONLY PURPOSE. -- Regards
-- Regards
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
participants (2)
-
Manjunath Goudreddy -
prince gosavi