YyyingYina

YyyingYina's Stars

• a171232886/TJUThesis_master_2021

  天大博士/硕士学位论文Latex模板，根据2021年版要求修改，可直接在Overleaf上运行。:star:所写的论文成功提交天津大学图书馆存档！（2021.12.24）

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• finafily526/A_Model_of_Risk_Control

  关于评分卡的基本流程

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• mncosta/biogeme_tutorial

  Introductory tutorial to Biogeme

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• basf/doe

  Python package for flexible generation of D-optimal experimental designs

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• cjsyzwsh/ASU-DNN

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• LianZS/spyderpro

  基于celery大规模爬虫

  Language:Python101

• YoungjuneKwon/forked-semopy

  forked from https://bitbucket.org/herrberg/semopy/src/master/

  Language:Python10315

• ulf1/bwsample

  Sampling algorithm for best-worst scaling sets.

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• SonghuaHu-UMD/Explainable_AI_Comparison

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• mbc96325/Mixture-logit-model-for-AV-adoption

  This is an archive of codes for paper "Impacts of subjective evaluations and use of existing travel modes on adoption of autonomous mobility-on-demand"

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• zarkaltair/Data-Scientist

  Repository when I learn Data Scientist

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• amirothman/scikit-learn-course

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• stevenkleinegesse/bedimplicit

  Source code for "Efficient Bayesian Experimental Design for Implicit Models" - https://arxiv.org/abs/1810.09912

  Language:Python2102

• StriderStranger/GeistDenkmal

  Do not go gentle into that good night !

  Language:Python2001

• switchingkeyboards/Stock-Return-Predictor

  Predicting stock return based on sector characteristics through GBRT, LSTM and NN

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• yangpingyan/ML

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• bencsn/artrater-backend

  A backend service written in python

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• carlos-echeverria/RobotTuples

  python script to generate robot tuples

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• fagan2888/Mixture-logit-model-for-AV-adoption

  This is an archive of codes for paper "Impacts of subjective evaluations and use of existing travel modes on adoption of autonomous mobility-on-demand"

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• jcmoody6/car-value

  Supplementary material for the working paper entitled "The Value of Car Ownership and Use in the United States"

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• MasaKat0/EfficientExperimentalDesign

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• ProtitiAnnesha/DissertationResearch

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• SukheshNuthalapati/BeeSnap-ML

  Repository for Machine Learning sub-team of the BeeSnap V.I.P. (Vertically Integrated Project).

  Language:Jupyter Notebook10

• TheCoolBoots/KDD_Final

  A custom implementation of Gradient Boosting, Linear Regression, and a Neural Network that predicts tomorrow's ETH price based on today's stock market performance

  Language:Python1