zero-dependency image processing library
python drawing geometry zig webassembly wasm image-processing zero-dependency svd-matrix-factorisation zig-package
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svd-matrix-factorisation
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A collection of differentiable SVD methods and ICCV21 "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
deep-learning pytorch style-transfer image-recognition svd fine-grained-classification svd-factorization fine-grained-visual-categorization svd-matrix-factorisation imagenet-classification iccv21 end-to-end-svd differentiable-svd
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Designed a movie recommendation system using content-based, collaborative filtering based, SVD and popularity based approach.
collaborative-filtering recommendation-system movie-recommendation movielens-dataset content-based-recommendation surprise-python hybrid-recommender-system svd-matrix-factorisation
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Differentiable matrix factorizations using ImplicitDifferentiation.jl.
automatic-differentiation matrix-factorization svd lu-decomposition qr-decomposition matrix-decompositions cholesky-decomposition svd-matrix-factorisation schur-decomposition eigendecomposition implicit-differentiation generalized-eigenvalue forward-mode-autodiff reverse-mode-autodiff
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- Julia
Recommend movies to users by RBMs, TruncatedSVD, Stochastic SVD and Variational Inference
restricted-boltzmann-machine cosine-similarity svd movie-recommendation recommend-movies svd-matrix-factorisation
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Singular Value Decomposition (SVD) is a fundamental linear algebra technique that factorizes any into the product of three matrices: are orthogonal matrices containing left and right singular vectors, while sigma is a diagonal matrix of non-negative singular values. It is essential for data reduction, noise removal, and matrix approximation.Solver
data-science machine-learning optimization linear-algebra solver matrix-factorization dimensionality-reduction svd singular-value-decomposition numerical-linear-algebra svd-factorization svd-matrix-factorisation svd-recommendation-algorithm svd-image-compression senatorov svd-solver pca-from-svd python-svd solver-svd
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- Python
Includes the SVD-based approximation algorithms for compressing deep learning models and the FPGA accelerators exploiting such approximation mechanism, as described in the paper Mapping multiple LSTM models on FPGAs.
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Projet d'étude système de recommendation en utilisant filtrage collaboratif
machine-learning machine-learning-algorithms neo4j-database recommendation-engine svd-factorization svd-matrix-factorisation svd-recommendation-algorithm system-recommender filtrage-collaboratif
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- Python
Code of Book Recommendation System, suggests books to users based on their interests and reading history along with the content of the item.
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This repo contains a machine learning model made using advanced and enhanced algos like KNN,SVD and also concepts like vectorization ,cosine similarity which predicts the similar movies for a given fav movie of user. So no more time wasting on searching for a good of you're choice
machine-learning movie-database cosine-similarity frontend-app movie-recommendation movies-api responsive-web-design knn-algorithm svd-matrix-factorisation tfidf-vectorizer linearkernel
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CVM Class Library
fortran linear-algebra matrix-factorization matrix-multiplication matrices blas vectors lapack eigenvalues cholesky-factorization svd-matrix-factorisation bunch-kaufman
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redsvd - RandomizED Singular Value Decomposition
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Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity
spark collaborative-filtering xgboost cosine-similarity upsampling jaccard-similarity tfidf content-based-recommendation surprise-python pearson-correlation xgboost-regression tf-idf-score svd-matrix-factorisation user-based-recommendation item-based-recommendation similar-items feature-augmentation
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- Python
This project demonstrates the application of Singular Value Decomposition (SVD) for image compression using Python and NumPy.
python machine-learning statistics numpy machine-learning-algorithms statistical-learning ml pca machinelearning svd acp singular-value-decomposition svd-factorization svd-matrix-factorisation svd-recommendation-algorithm svd-image-compression
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Coursework for CS550 : Massive Data Mining. Topics covered include Map-Reduce, Association Rules, Frequent Itemsets, Locality-Sensitive Hashing (LSH), Singular Value Decomposition (SVD), Page Rank, k-means, Modularity, Spectral Clustering, Clique-based communities, Clustering Data Streams.
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PISSA-Without-regret is Pissa used with Lora-Without-Regret blog optimal configuration. We provide comparisons to LoRA and FullFT using the same regime.
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Building a Collaborative Filtering based Recommender system using e-commerce data.
matrix-factorization recommendation-engine recommender-systems svd-matrix-factorisation nmf-matrix-factorization
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Toy example of a tool to optimize CNN layers widths, according their SVD decomposition
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Sparse Truncated SVD Benchmark (Python)
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- Jupyter Notebook
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