Shutong (dingshutong)

dingshutong

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Location:Geneva

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Shutong's starred repositories

azure-search-vector-samples

A repository of code samples for Vector search capabilities in Azure AI Search.

Language:Jupyter NotebookLicense:MITStargazers:708Issues:0Issues:0

Deep-Learning-Specialization

deeplearning.ai on Coursera

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dlaicourse

Notebooks for learning deep learning

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dsdc

DSD Constructor is a very simple, standalone tool, which is able to create and edit DSDs and their related artefacts (i.e. concept schemes and code lists) in order to generate a DSD which fits your needs and can be used, for example, by SMART to obtain the output dataset as required.

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TensorFlow-Tutorials

TensorFlow Tutorials with YouTube Videos

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ecoicop_classification

Examination of the possibility of using ML methods in official statistics (project as part of UNECE High Level Group for Modernization of Official Statistics - Machine Learning)

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smart

SMART allows users to generate and automate the production of analytical reports defined by means of a SDMX Data Structure Definition (DSD), either from processing micro-level data or from aggregated data by means of transcoding.

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GenericValidationRules

Draft implementations of generic validation rules in R-validate syntax

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VTL

VTL Engine and Editor

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nada

National Data Archive (NADA) is a web-based cataloging system that serves as a portal for researchers to browse, search, compare, apply for access, and download relevant census or survey information. It was originally developed to support the establishment of national survey data archives.

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nada

National Data Archive (NADA) is an open source data cataloging system that serves as a portal for researchers to browse, search, compare, apply for access, and download relevant census or survey information. It was originally developed to support the establishment of national survey data archives.

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ReadStat

Command-line tool (+ C library) for converting SAS, Stata, and SPSS files 💾

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codemirror5

In-browser code editor (version 5, legacy)

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AdvBayesLearnCourse

Course material for the PhD course Advanced Bayesian Learning at Linköping University

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