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From Local to Global: A Graph RAG Approach to Query-Focused Summarization. A new future of work: The race to deploy AI and raise skills in Europe and beyond. Multi-PaperCompare & …

The Research Flow (RFlow) is a Python framework for creating Directed Acyclic Graph (DAG) workflows. The project's goal is to remove boilerplate code from common machine learning stages like data preprocessing, model fitting and evaluation.

Rflow is an R package providing R users with a general-purpose workflow framework. Rflow allows you to describe your data declaratively as objects with dependencies and does the heavy lifting for you.

R-Flow is a software product that uses R to analyze data in a workflow. R-Flow can automatically perform R analysis by selecting only the R function Task icon without RScript creation.

2022年7月1日 · Prominent statistician Frank Harrell has come out with a radically new R tutorial, rflow. The name is short for “R workflow,” but I call it “R in a box” –everything one needs for beginning serious usage of R, starting from little or no background.

rflow - Pipeline Interface for TensorFlow in R. This is an experimental and work-in-progress R library for easily using Google TensorFlow, inspired by Google skflow package. This package aims to help R users to easily build popular deep learning models as well as customized models with flexible and desired deep architectures.

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rflow is a package that allows cacheing of functions in memory, on disk or in both memory and disk. A common problem when processing data as part of a pipeline is avoiding unnecessary calculations.