Search Results for "r-4.1.3-win.exe"
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Showing 6 open source projects for "r-4.1.3-win.exe"
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ZIO
A type-safe, composable library for async and concurrent programming
ZIO is a purely functional, type-safe Scala library that provides an Effect (ZIO[R,E,A]) abstraction for asynchronous, concurrent programming. It offers resource safety, fiber-based concurrency, strong error handling, and deterministic testing—all with zero external dependencies. Ideal for building scalable backend systems with compositional architecture. -
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Apache Spark
A unified analytics engine for large-scale data processing
...The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
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osm4scala
Reading OpenStreetMap Pbf files.
Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files. -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction.... -
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Waterloo
Java-based scientific graphics
Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab. -
6
Deem
Analyze time-course data with significance tests, clustering, modeling
...Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional currently. The app was and is developed at the University of Rochester (http://cbim.urmc.rochester.edu) under the GPL 3.0 license. This is a fork of that project.
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