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The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
The Overhead Imagery Research Data Set (OIRDS) is a collection of an open-source, annotated, overhead images that computer vision researchers can use to aid in the development of algorithms. [1] Most computer vision and machine learning algorithms function by training on a large set of example data. [ 2 ]
CakeML is a REPL version of ML with formally verified runtime and translation to assembler. Isabelle (Isabelle/ML Archived 2020-08-30 at the Wayback Machine) integrates parallel Poly/ML into an interactive theorem prover, with a sophisticated IDE (based on jEdit) for official Standard ML (SML'97), the Isabelle/ML dialect, and the proof language ...
The SDMX converter is an open source application that offers the ability to convert DSPL (Google's Dataset Publishing Language) messages to SDMX-ML, and vice versa. The output file of a DSPL dataset is a zip file containing data (in the form of CSV files) and metadata (as an XML file). Datasets in this format can be visualized in the Google ...
Data analysis typically involves working with smaller, structured datasets to answer specific questions or solve specific problems. This can involve tasks such as data cleaning, data visualization, and exploratory data analysis to gain insights into the data and develop hypotheses about relationships between variables. Data analysts typically ...
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply.
In June, it bought the open-source generative AI startup MosaicML for $1.4 billion. [ 18 ] [ 19 ] In October, Databricks bought data replication startup Arcion for $100 million. [ 20 ] In what is believed to be its sixth acquisition, Databricks bought Tabular, a data-management system used by open source AI, for over $1 billion.
In machine learning (ML), boosting is an ensemble metaheuristic for primarily reducing bias (as opposed to variance). [1] It can also improve the stability and accuracy of ML classification and regression algorithms. Hence, it is prevalent in supervised learning for converting weak learners to strong learners. [2]