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The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged [3] even though the RDD API is not deprecated. [4] [5] The RDD technology still underlies the Dataset API. [6] [7]
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark; Data frames in the R programming language; Frame (networking)
Word2vec was created, patented, [7] and published in 2013 by a team of researchers led by Mikolov at Google over two papers. [1] [2] The original paper was rejected by reviewers for ICLR conference 2013. It also took months for the code to be approved for open-sourcing. [8] Other researchers helped analyse and explain the algorithm. [4]
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SPARK is a formally defined computer programming language based on the Ada programming language, intended for the development of high integrity software used in systems where predictable and highly reliable operation is essential. It facilitates the development of applications that demand safety, security, or business integrity.
Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.
[1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical simulations. [1] As a result of these tradeoffs, row-oriented formats are more commonly used in Online transaction processing (OLTP) and column-oriented formats are more commonly used in Online analytical processing ...
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]