HarryZhu (harryprince)

harryprince

Geek Repo

Company:Mobike

Location:Jilin University of Finance and Economics

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Organizations
r-spark

HarryZhu's repositories

geospark

bring sf to spark in production

awesome-rmarkdown

An awesome rmarkdown related package collection

awesome-sparklyr

An awesome sparklyr related package collection

awesome-leaflet

An awesome leaflet related package collection

awesome-apache-airflow

Curated list of resources about Apache Airflow

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Ax

Adaptive Experimentation Platform

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EasyRL

EasyRL

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gdal-tiler

A customisable Python + GDAL slippy map tile builder

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GeoSparkSim

Scalable Microscopic Traffic Simulation

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modeltime.gluonts

GluonTS Deep Learning with Modeltime

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contextual

Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies

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cvxpylayers

Differentiable convex optimization layers

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dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

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euler

A distributed graph deep learning framework.

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GraphSAGE

Representation learning on large graphs using stochastic graph convolutions.

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grf

Generalized Random Forests

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logitr

Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations in R

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mapdeck

R interface to Deck.gl and Mapbox

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ParMETIS

ParMETIS - Parallel Graph Partitioning and Fill-reducing Matrix Ordering

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PGL

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

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probability

Probabilistic reasoning and statistical analysis in TensorFlow

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Reco-papers

Classic papers and resources on recommendation

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rmpk

Mixed Integer Linear and Quadratic Programming in R

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Robyn

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.

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sparktf

R interface to Spark TensorFlow Connector

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the-r-in-spark

The R in Spark: Learn Apache Spark using R

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