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ddbourgin / numpy-ml

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Installation not documented; couldn't find PyPi package or run tests

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dmyersturnbull
dmyersturnbull commented May 1, 2020

This is an awesome library, thanks @ddbourgin!!

Users might not know the best way to install this package and try it out. (I didn't, so I eventually just copied the source files.)
Neither the readme nor readthedocs have install instructions.

I couldn't find it on PyPi or Anaconda, and there doesn't appear to be a pyproject.toml, setup.cfg, setup.py, or conda recipe.

Moreover, the t

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MaurizioFD / RecSys2019_DeepLearning_Evaluation

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This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches"

deep-learning neural-network reproducible-research collaborative-filtering matrix-factorization hyperparameters bpr recommendation-system recommender-system reproducibility recommendation-algorithms knn matrix-completion evaluation-framework content-based-recommendation hybrid-recommender-system funksvd bprmf bprslim slimelasticnet
  • Updated Jun 18, 2020
  • Python

arnaldog12 / Machine_Learning

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Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

python machine-learning neural-network naive-bayes linear-regression machine-learning-algorithms regression feature-selection logistic-regression kmeans adaboost decision-trees polynomial-regression knn principal-component-analysis redes-neurais-artificiais linear-discriminant-analysis multilinear-regression
  • Updated Mar 21, 2019
  • Jupyter Notebook

gasevi / pyreclab

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pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab.

rating svd knn implicit-feedback rating-prediction recommendation-algorithm alternating-least-squares
  • Updated May 9, 2020
  • C++

jayshah19949596 / Machine-Learning-Models

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Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

neural-network random-forest linear-regression machine-learning-algorithms naive-bayes-classifier supervised-learning gaussian-mixture-models logistic-regression kmeans decision-trees knn principal-component-analysis dynamic-time-warping kmeans-clustering em-algorithm kmeans-algorithm singular-value-decomposition knn-classification gaussian-classifier value-iteration-algorithm
  • Updated May 15, 2017
  • MATLAB

MBKraus / Predicting_real_estate_prices_using_scikit-learn

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Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

real-estate python machine-learning neural-network random-forest lasso xgboost polynomial ensemble-learning ols decision-trees ridge-regression polynomial-regression knn multi-layer-perceptron amsterdam predicting-housing-prices lasso-regression mlp-regressor knn-regression
  • Updated Apr 9, 2019
  • Python

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