Discover @sv6375261073 Open Source projects

Shivam Vishwakarma (@sv6375261073)

sv6375261073

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Registered almost 7 years ago
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Location 🇮🇳 India
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Legal_laws-classification

It is able to classify texts into their related laws of government .

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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 .

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socket

chat app using socket

Decision-tree-algo-implementation-with-math

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scrapperSV

Scrappin Facebook, Instagram, Twitter, Whatsapp automation, google images , altnews,vishwas news .

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ProductRecommendationAlgo_ApproriAlgo

its the implementation of Approri algo for product recommendation as customer buy related product of other product . Example relevent product of each other

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K-MEAN-clustering-with-mathematics-

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mathmatics_research_diagrams_with_mlf_Function

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RIET_AI_SHIVAM_RAJAT_ASHUVNITENDER_OMPRAKASH__NewsTopicsClassification

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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 pca

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Symbol-Table-in-compiler

Ecommerce_webApp-Django

NaiveBayesAlgoImplementationwithjointprobablity

its a mathmetical implementation of naive bayes with joint probablity

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GaussianNB-Algo-Implementation-with-math

This is a classifier based on probablity of samles it find the most closet value of a sample by calulating probablity

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porn_text_detection

This model is able to detect whether a text is unwanted or not.

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Linear-Regression

its a mathematical implementation of linear Regression

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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 .

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