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For further details check the project's GitHub repository or the Hugging Face dataset cards (taskmaster-1, taskmaster-2, taskmaster-3). Dialog/Instruction prompted 2019 [340] Byrne and Krishnamoorthi et al. DrRepair A labeled dataset for program repair. Pre-processed data Check format details in the project's worksheet. Dialog/Instruction ...
The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Metadata is a data Dictionary of definitions to set up and display the notebook. Notebook Format is a version number of the software. List of cells are different types of Cells for Markdown (display), Code (to execute), and output of the code type cells. [23]
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
Environment for DeveLoping KDD-Applications Supported by Index-Structures is a similar project to Weka with a focus on cluster analysis, i.e., unsupervised methods. H2O.ai is an open-source data science and machine learning platform; KNIME is a machine learning and data mining software implemented in Java.
Cypher is a declarative graph query language that allows for expressive and efficient data querying in a property graph. [1]Cypher was largely an invention of Andrés Taylor while working for Neo4j, Inc. (formerly Neo Technology) in 2011. [2]
GraphQL: an open-source data query and manipulation language for APIs. Dgraph implements modified GraphQL language called DQL (formerly GraphQL+-) Gremlin: a graph programming language that is a part of Apache TinkerPop open-source project [51] SPARQL: a query language for RDF databases that can retrieve and manipulate data stored in RDF format
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R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.