Knowledge extraction through Data Analysis, including Locality Sensitive Hashing (LSH).
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Updated
Jun 11, 2022 - Jupyter Notebook
Knowledge extraction through Data Analysis, including Locality Sensitive Hashing (LSH).
Deep Neural Net For Finding Similar Images With Hyperparameter Optimization + AWS And Azure GPU Capabilities
Statistics is a command line tool for computing distance and data normalization
Raku package for the computation of various distance functions.
Fast pairwise cosine distance calculation and numba accelerated evolutionary matrix subset extraction 🍐🚀
Implemented various spellcheck techniques like cosine similarity, jaccard similarity and levenshtein distance. Open to any further contributions.
Intrusion Detection System and Serbian family relationships
IR implemented by using TF-IDF method
This repo contains the movie recommender system which uses vectorization, cosine similarity distance methods to calculate the most similar content based on movie tags/info.
Système de recommandation
wordvector demonstration with spacy.
Big data homework solutions
The purpose of this project is to connect an ontology(from Protégé) to RStudio and retrieve the details of each class of the ontology on which we have analysed and retrived 5 keywords for each class using tf–idf and also calculate the page rank based on a query search using cosine distance.
Classification of IRIS Dataset using various distance metrics.
Content-based recommendation engine using Python and Scikitlearn, using concepts of Cosine distance and Euclidean distance. Finally, by using IMDB 5000 movie dataset built a content-based recommendation engine using CountVectorize and Cosine similarity scores between movies.
This program calculates the distances between coordinates using a possible of three formulas: Vincenty, Cosines, or Haversine.
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