Machine Learning

blog

Model Monitoring with R Markdown, pins, and RStudio Connect

April 8, 2021 |

Model monitoring is a key component of ModelOps, and the R ecosystem offers flexible, code-first solutions that meet the model monitoring needs of data science practitioners.

blog

RStudio Named Strong Performer in the Forrester Wave™: Notebook-Based Predictive Analytics and Machine Learning, Q3 2020

September 25, 2020 |

Read The Forrester Wave™: Notebook-Based Predictive Analytics and Machine Learning, Q3 2020 Report to learn why RStudio was named a Strong Performer by this independent research firm, and received the highest scores possible in the evaluation criteria of security, apps, open source and platform infrastructure.

rstudio::conf 2019

Why TensorFlow eager execution matters

January 25, 2019 |

In current deep learning with Keras and TensorFlow, when you've mastered the basics and are ready to dive into more involved applications (such as generative networks, sequence-to-sequence or...

rstudio::conf 2019

Push straight to prod API development with R and Tensorflow at T-Mobile

January 24, 2019 |

When tasked with creating the first customer-facing machine learning model at T-Mobile, we were faced with a conundrum.

rstudio::conf 2019

Introducing mlflow

January 24, 2019 |

We introduce the R API for MLflow, which is an open source platform for managing the machine learning lifecycle. We demonstrate each component of the platform–Tracking, Projects, and...

Webinars

Training your TensorFlow models in the cloud

April 25, 2018 |

TensorFlow is an open-source software library for numerical computation using data flow graphs.

rstudio::conf 2018

Machine Learning with R and TensorFlow

February 4, 2018 |

In this talk we’ll explore the use of TensorFlow from R, describing the complete workflow including data ingestion, training, and deploying models into production.

Webinars

Creating and Preprocessing a Design Matrix with Recipes

June 8, 2017 |

In this talk, a new package called recipes is shown where the specification of model terms and preprocessing steps can be enumerated sequentially.