Search Results for "software without code"
Sort By:
Showing 25 open source projects for "software without code"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
magrittr
Improve the readability of R code with the pipe
magrittr introduces the pipe operator (%>%) and related functional utilities into R. It underlies the powerful piped syntax widely adopted in tidyverse workflows by enabling left-hand argument passing and providing helpers like compound assignment pipes and exposition pipes. -
2
box
Write reusable, composable and modular R code
box is an R package providing a modular system / module loader for organizing reusable R code outside of full packages. It allows users to treat R scripts (files/folders) as modules — possibly nested — with explicit exports, imports, and scoping. The idea is to let users structure code in a more modular, composable way, without needing every reusable component to be a full CRAN-style package. It also provides a cleaner syntax for importing functions or modules (via box::use) that allows scoping control and avoids global pollution. ... -
3
lintr
Static Code Analysis for R
lintr is a static code analysis tool for R that identifies syntax errors, style inconsistencies, and other potential issues in R scripts and packages. It supports customizable lint rules and integrates with many editors to provide realtime feedback and enforce coding standards (e.g., tidyverse style). -
4
Shiny
Build interactive web apps directly from R with Shiny framework
Shiny is an R package from RStudio that enables users to build interactive web applications using R without requiring knowledge of JavaScript, HTML, or CSS. It allows statisticians and data scientists to turn their analyses into fully functional web dashboards with reactive elements, data inputs, visualizations, and controls, making data communication more effective and dynamic. -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
5
future
R package: future: Unified Parallel and Distributed Processing in R
The future package in R provides a unified abstraction for asynchronous and/or parallel computation. It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. It handles automatic exporting of needed global variables/functions, managing of packages, RNG, etc. Automatic detection and export of global objects and functions needed by future expressions, so the user doesn’t need to manage that manually. ... -
6
R Source
Read-only mirror of R source code
The wch/r-source repository is a read-only mirror of the official R language source code, maintained to reflect the upstream Subversion (SVN) R core development tree. This mirror provides public visibility into R’s internals—everything from the interpreter, base and recommended packages, documentation, and C/Fortran code under the hood. It is updated hourly to stay in sync with the upstream SVN. Although it mirrors the R source for browsing and reference, it is not the “canonical development... -
7
plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
8
purrr
A functional programming toolkit for R
purrr enhances R’s functional programming capabilities by providing a consistent set of tools for working with lists and vectors, enabling safer and more expressive iteration compared to base R’s loop functions. -
9
blogdown
Create Blogs and Websites with R Markdown
blogdown is an R package that enables the creation and maintenance of static websites and blogs using R Markdown and Hugo (or other static-site generators). Developed by Yihui Xie and team, it provides functions to initialize sites, write posts, manage themes, and deploy with minimal fuss. It seamlessly blends R code chunks and web content, ideal for data storytellers and technical bloggers. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
10
pkgdown
Generate static html documentation for an R package
pkgdown is an R package (by the r-lib group) whose purpose is to generate static websites (HTML) for R packages, automatically converting a package’s help files, vignettes, README, NEWS, etc., into a documentation website. It helps package authors share their documentation online with minimal friction. It supports custom templates, themes, and configuration. pkgdown 2.0.0 includes an upgrade from Bootstrap 3 to Bootstrap 5, which is accompanied by a whole bunch of minor UI improvements. If... -
11
Advanced Shiny
Shiny tips & tricks for improving your apps and solving common problem
The advanced-shiny repository is a curated collection of practical tips, design patterns, and mini Shiny apps focused on solving real-world challenges in R Shiny applications. The author (Dean Attali) collected many of the “harder” or less-documented tricks he uses or encounters frequently—things like controlling UI behavior dynamically, managing reactive logic, optimizing interactivity, and structuring large Shiny codebases. The repo’s structure includes folders of example apps each... -
12
plumber
Turn your R code into a web API
plumber is an R package that enables rapid creation of HTTP APIs by decorating existing R functions with special roxygen-style comments. It transforms R scripts into RESTful web services with minimal setup and integrates easily with RStudio or CI environments. -
13
clusterProfiler
A universal enrichment tool for interpreting omics data
...The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. Results are returned in tidy, manipulation-friendly structures and pair naturally with rich visualization functions (via companion tooling) to summarize pathways, terms, and gene–set relationships. -
14
rollama
Wrap the Ollama API, which allows you to run different LLMs
rollama is an R package that provides a convenient interface for interacting with local large language models through the Ollama API, bringing modern AI capabilities into the R ecosystem. It is designed to make LLM usage accessible to data scientists and researchers who work primarily in R, allowing them to generate text, analyze data, and create embeddings without relying on external cloud services. The package emphasizes reproducibility and privacy by enabling local execution of models,... -
15
gptstudio
GPT RStudio addins that enable GPT assisted coding, writing & analysis
gptstudio is an R package and RStudio Addins interface that enables interactive use of large language models (OpenAI, HuggingFace, etc.) from within R. It includes a Chat add-in and source editing helpers to query models, generate code, comment or refactor code, and manage conversations—all integrated into RStudio using Shiny and bslib. -
16
QBPWCF
PHP library for not only web-based application in Fedora Linux
此專案的目的是要建立簡單、易用、參數說明完整且富有調整性的PHP元件庫，讓PHP程式設計開發者可以輕鬆地建立高度客製化的應用。 套用當代的術語而言，就是要作為LOW CODE平台的函式庫。 -
17
Statistical Rethinking 2024
This course teaches data analysis
The 2024 repository is the most recent version of the course, reflecting ongoing refinements in pedagogy, statistical modeling techniques, and coding practices. It provides updated notebooks, R scripts, and model examples, some streamlined and restructured compared to previous years. The 2024 repo also highlights the transition toward more robust Stan models and integration with newer Bayesian workflow practices, continuing to emphasize accessibility for learners while modernizing the tools.... -
18
Statistical Rethinking 2023
Statistical Rethinking Course for Jan-Mar 2023
The 2023 edition modernizes and expands on the same curriculum, adjusting exercises and code for newer versions of R, Stan, and supporting packages. It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following... -
19
AI-Agent-Host
The AI Agent Host is a module-based development environment.
The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI... -
20
R Packages (r-pkgs)
Building R packages
...The book teaches how to develop, document, test, and share R packages: the practices, tools, infrastructure, workflows, and best practices around package development in R. The repository contains the code, text, site content for building the book, examples, exercises, etc. It is not a software library to be loaded in R (except perhaps the examples), but a resource/guide/manual. The first edition is no longer available online. A second edition is under development and available. -
21
Statistical Rethinking 2022
Statistical Rethinking course winter 2022
This repository hosts the 2022 version of the Statistical Rethinking course. It contains course materials such as R scripts, notebooks, and worked examples aligned with McElreath’s textbook. The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a... -
22
Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
23
benchm-ml
A benchmark of commonly used open source implementations
This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different... -
24
DataScienceR
a curated list of R tutorials for Data Science, NLP
The DataScienceR repository is a curated collection of tutorials, sample code, and project templates for learning data science using the R programming language. It includes an assortment of exercises, sample datasets, and instructional code that cover the core steps of a data science project: data ingestion, cleaning, exploratory analysis, modeling, evaluation, and visualization. Many of the modules demonstrate best practices in R, such as using the tidyverse, R Markdown, modular scripting,... -
25
Investing
Investing Returns on the Market as a Whole
This repository, owned by the user zonination (Zoni Nation), presents a data visualization and analysis project on long-term returns from broad stock market indexes, especially the S&P 500. The author gathers historical price data (adjusted for inflation and dividends) and computes growth trajectories under a “buy and hold” strategy over decades. The key insight illustrated is that over sufficiently long holding periods (e.g. 40 years), the stock market stabilizes and nearly always yields...
- Previous
- You're on page 1
- Next