Daniel Falbel

Senior Software Engineer at Posit, PBC

dfalbel.github.io

dfalbel.bsky.social

dfalbel

0009-0006-0143-2392

I am a software engineer at Posit PBC based in Brazil. I work on open-source tools at the intersection of R and machine learning, including torch , keras , and the broader mlverse ecosystem. I also contribute to packages like reticulate and other projects that bridge R and Python.

Software by Daniel Falbel#

Posts and resources by Daniel Falbel#

What’s New in the Torch Ecosystem - posit::conf(2023)

Presented by Daniel Falbel torch is an R port of PyTorch, a scientific computing library that enables fast and easy creation and training of deep learning models. In this talk, you will learn about the latest features and developments in torch, such as luz, a higher-level interface that simplifies your model training code, and vetiver, a new integration that allows you to deploy your torch models with just a few lines of code. You will also see how torch works well with other R packages and tools to enhance your data science workflow. Whether you are new to torch or already an experienced user, this talk will show you how torch can help you tackle your data science challenges and inspire you to build your own models. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Lightning talks. Session Code: TALK-1163

Daniel Falbel

RStudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny RMarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source OSS Quarto Posit Python ML

Daniel Falbel | What’s new in TensorFlow for R | RStudio (2020)

TensorFlow is the most popular open-source platform for machine learning and it’s ecosystem is evolving incredibly fast. In this talk we will explore what’s new in TensorFlow 2.0 as well as how to build data pre-processing pipelines using the tfdatasets package and how to use pre-trained models with tfhub

Daniel Falbel