A webapp for recommending movies based on two models: collaborative filtering with non-negative matrix factorisation and k-nearest neighbours algorithm.
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Updated
Aug 31, 2021 - Python
A webapp for recommending movies based on two models: collaborative filtering with non-negative matrix factorisation and k-nearest neighbours algorithm.
An exercise on the use of NMF for Blind Signal Separation
This project, done for GA Tech, explores relationship between health factors and hospitalization in NHANES dataset
Scientific Comparison of Algorithms
NLP | Python
Seminary of Computational Engineering (University of Aveiro 2021/2022)
Projet de NLTP comparant des approches supervisées et non supervisées dans le cadre de la formation d'ingénieur machine Learning dispensé par Openclassrooms
Détection de sujets d’insatisfaction des clients d'une entreprise
archR: Identifying promoter sequence architectures de novo using NMF
A Movie Recommender using Python and Flask with both non-negative matrix factorization (NMF) and collaborative filtering models
Non-negative matrix factorization method
Non-Negative Matrix Factorization analysis of 1890 editions of Emily Dickinson's poetry
This project uses NLP and NMF techniques for topic modeling on movie reviews. It reads a CSV file, cleans text by removing stopwords & lemmatizing words, vectorizes using TfidfVectorizer, and extracts 10 topics with NMF. The code can be adapted to work with any domain's dataset.
Sklearn, PCA, t-SNE, Isomap, NMF, Random Projection, Spectral Embedding
Topic modeling with python and sckit-learn
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