A Python package that helps in evaluating text content.Details
App that helps in generating synthetic data using the R package conjurer.Details
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This is the official documentation of Python package indepth and is currently a work in progress document. Please come back later to find the completed documentation. Table of contents Overview Installation remov_punct wrdCnt vocabSize commonWrd realWrds MostSimilarSent sbjVrbAgreement modalRuleError PrpDonot VrbTenseAgreementError a_an_error motionVerbs coherentWrds hyponymPolysem_cnt concretMeaningPOS buildFeatures Overview This package is a collection of functions that aim to enable the user to perform non-trivial tasks in realm of natural language processing.
About the app Installation guide Documentation References Source code License Feedback guidelines Go to about section How to install User Guide References GitHub License Contribute Demo About the app This is a PowerBI application with R script driven visual. This app attempts to help in generating topics and sentiment from text data field by writing low or no code at all.
This article provides a perspective for building a simple staff scheduler app as demonstrated here. Note: The author focuses on the reasoning behind the code and therefore detailed code explanation is out of scope. Readers with working knowledge of R language would benefit the most from this article. Table of contents: Motivation Business problem Data Components of building a staff scheduler R code Concluding remarks 1. Motivation From open source algorithms such as glpk to commercial ones such as Gurobi, there are many options available to solve optimization problems.