MimesisMimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.
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Mutual labels: datascience, synthetic-data
PopEDPopulation Experimental Design (PopED) in R
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Mutual labels: population, population-model
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HackyHourHandbookA handbook for those who want to start coordinating Hacky Hour events in their University/Institute
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Mutual labels: datascience
MixingBearPackage for automatic beat-mixing of music files in Python 🐻🎚
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Mutual labels: algorithm-library
noisy-K-FACNatural Gradient, Variational Inference
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Mutual labels: bayesian-inference
game-feature-learningCode for paper "Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery", Ren et al., CVPR'18
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Mutual labels: synthetic-data
pack📦 lightweight rectangle packing algorithm
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Mutual labels: combinatorial-optimization
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Mutual labels: combinatorial-optimization
NetBIDData-driven Network-based Bayesian Inference of Drivers
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Mutual labels: bayesian-inference
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Mutual labels: bayesian-inference
augraphyAugmentation pipeline for rendering synthetic paper printing, faxing, scanning and copy machine processes
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Mutual labels: synthetic-data
Decision Analysis Course🎓 Uni-Bonn Decision Analysis graduate course, lectures and materials
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Mutual labels: bayesian-inference
ETL-Starter-Kit📁 Extract, Transform, Load (ETL) 👷 refers to a process in database usage and especially in data warehousing. This repository contains a starter kit featuring ETL related work.
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Mutual labels: datascience
uoaisCodes of paper "Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling", ICRA 2022
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LingoInfer the gender of an individual based on their name.
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Mutual labels: bayesian-inference
r-resources-for-data-scienceA biggest collection of free books and other resources for R programming
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Mutual labels: datascience
lgprR-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.
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Mutual labels: bayesian-inference