October 28, 2016

Introducing the Algorithmia R Client

Algorithmia now has an R Client for developersToday, we’re excited to announce full development support for R on Algorithmia with our new CRAN package.

R users now have access to Algorithmia’s library of more than 2,500 algorithmic microservices via the client.

With the new client, R users can now deploy their predictive models and analytical routines as production-ready API’s without ever having to provision, configure, or manage servers or infrastructure.

Quick Links: CRAN Package | Docs | Client Guide | R Development Guide

Algorithmia was founded on the belief that our job is to empower developers with the tools to extract insights from their data in production environments.

“R has been synonymous with data analysis, statistics, and graphical modeling,” Diego Oppenheimer says, Algorithmia founder and CEO. “Until recently, most R users lived in academia and research. But, as data scientists have moved into industry, they’ve brought their tool of choice with them.”

We want to ensure your most important contributors aren’t distracted with tasks like setting up infrastructure, fighting with libraries, or managing dependencies. We've created a sample sentiment analysis forecasting pipeline in R to demonstrate how easy R + Algorithmia development can be. This recipe uses the Sentiment Time Series microservice to process unstructured text and return a sentiment time series plot and frequency to help enterprises understand their customer data.

This is why we’re excited to be providing researchers, developers, and data scientists with enterprise-grade tools for leveraging Algorithmia in their analysis, as well as deploying their R models to production.

“It’s clear to us that supporting R users with access to the algorithms on Algorithmia is crucial to our success of fulfilling our mission to make state-of-the-art algorithms discoverable and accessible to everyone.”

Using R and Algorithmia

We fit your workflow so you can spend more time doing data science:

  1. Access. Use any of the algorithms or microservices from our ever-growing library in your R projects. Install the Algorithmia package and you’re good to go.
  2. Develop. Work on your models and routines in the environment you’re comfortable with.
  3. Deploy. When you’re ready, instantly deploy them as production-ready microservices to our scalable cloud infrastructure.
  4. API’s. Call any algorithm or microservice via our clients for Java, Scala, Python, JavaScript, Node.js, Ruby, Rust, CLI, cURL and, of course, R.

R users can now utilize the entire Algorithmia library of microservices, no matter the programming language, in their R projects and then deploy them as production-ready APIs for their engineering team to use.

And, since we support Caffe, TensorFlow, and Theano, R users also have access to our cloud-based GPUs and deep learning models, like Places365 Classifier, Illustration Tagger, InceptionNetCaffeNet, or DeepFilter.

More About Algorithmia

We’ve created an open marketplace for algorithms and algorithm development, making state-of-the-art algorithms accessible and discoverable by everyone.

On Algorithmia, algorithms run as containerized microservices that act as the building blocks of algorithmic intelligence developers can use to create, share, and remix at scale.

By making algorithms composable, interoperable, and portable, algorithms can be written in any supported language, and then made available to application developers where the code is always “on,” and available via a simple REST API.

Application developers can access the API via our clients for Java, Scala, Python, JavaScript, Node.js, Ruby, Rust, CLI, and cURL. We also have an AWS Lambda blueprint for those working on IoT-type projects.

Useful Links: Developer Center | API Docs | Press

Algorithmia is the largest marketplace for algorithms in the world, with more than 30,000 developers leveraging 2,500 algorithms. Algorithms and models on Algorithmia include research from MIT, University of Washington, Carnegie Mellon University, University of California Berkeley, Caltech, University of Texas at Austin, University of Tokyo, University of Toronto, among others.

Let us know what you think
If you run into any issues, or just want us to geek out about R with us, please reach out.

R u excited? Let us know @Algorithmia.

Matt Kiser

Matt Kiser

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