Open vikasreddy636 opened 2 years ago
thank u dude
should we study the mathematical part to memorize?
i am not sure about it
If there are any doubts regarding the code, I have updated all the documentation of all the classifiers in the code itself with all the links.
dear, i am unable to find the code in github.guid me
On Sun, Apr 17, 2022 at 10:43 PM Ginne vikas Reddy @.***> wrote:
If there are any doubts regarding the code, I have updated all the documentation of all the classifiers in the code itself with all the links.
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elham mohammadi master of Robotic engineering at Università di Genova Italy
hi guys ,sorry for the dealy i am in to the links next two days i am free till the exam so any time i am available ok.
so, finally, we came to the end of the project here are a few links to each and everything we have used, hope it might be useful :)
feature extractors LNIP(feature extractor) I am preparing the mathematical part I will try to explain LNIP Classifiers MLP Optimized RBF kernal linear SVM Random Forest XG Boost Nave Bayes
And the report might be useful.
Let's rock this guysssssss!!!!!!!!!!