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Legal_laws-classification
It is able to classify texts into their related laws of government .personality_detection
To know the behaviour , Characters of a person based on text relevant to him , like taking text from his Linkedin profile, facebook, twitter. it will take text enough of a person and will check some limitation that text(checking text that actually text includes required features or garbage text ) if text is proper it will return set of attributes of a person in percentage .socket
chat app using socketDecision-tree-algo-implementation-with-math
scrapperSV
Scrappin Facebook, Instagram, Twitter, Whatsapp automation, google images , altnews,vishwas news .ProductRecommendationAlgo_ApproriAlgo
its the implementation of Approri algo for product recommendation as customer buy related product of other product . Example relevent product of each otherK-MEAN-clustering-with-mathematics-
mathmatics_research_diagrams_with_mlf_Function
RIET_AI_SHIVAM_RAJAT_ASHUVNITENDER_OMPRAKASH__NewsTopicsClassification
bank_dataset
python_applications
frequency-of-each-char-in-a-file-
Character-sorting-with-ascii-prime-and-Composit-numbers-Algo
legal_document_clustering
Clustering document with kmean,doc2vec and pcaSymbol-Table-in-compiler
Ecommerce_webApp-Django
NaiveBayesAlgoImplementationwithjointprobablity
its a mathmetical implementation of naive bayes with joint probablityGaussianNB-Algo-Implementation-with-math
This is a classifier based on probablity of samles it find the most closet value of a sample by calulating probablityporn_text_detection
This model is able to detect whether a text is unwanted or not.FewShotLearning-NLP
Few Shot learning is very good concept in which even we have very few sample of a class we can get good accuracy . In this we match a class with other samples whether a sample match with other sample or not . if samples match we assign then True/0 else 1 .Love Open Source and this site? Check out how you can help us