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Chat with AI in RStudio

Interact with Github Copilot and OpenAI's GPT (ChatGPT) models directly in RStud...

News from the sparkly-verse

Highlights to the most recent updates to `sparklyr` and friends

Introducing Keras 3 for R

We are thrilled to introduce {keras3}, the next version of the Keras R package. ...

sparklyr 1.7: New data sources and spark_apply() capabi...

Sparklyr 1.7 delivers much-anticipated improvements, including R interfaces for ...

Convolutional LSTM for spatial forecasting

In forecasting spatially-determined phenomena (the weather, say, or the next fra...

Forecasting El Niño-Southern Oscillation (ENSO)

El Niño-Southern Oscillation (ENSO) is an atmospheric phenomenon, located in the...

Simple audio classification with torch

This article translates Daniel Falbel's post on "Simple Audio Classification" fr...

torch, tidymodels, and high-energy physics

Today we introduce tabnet, a torch implementation of "TabNet: Attentive Interpre...

First mlverse survey results – software, applications, ...

Last month, we conducted our first survey on mlverse software, covering topics r...

Introductory time-series forecasting with torch

This post is an introduction to time-series forecasting with torch. Central topi...

torch time series continued: A first go at multi-step p...

We continue our exploration of time-series forecasting with torch, moving on to ...

torch time series, take three: Sequence-to-sequence pre...

In our overview of techniques for time-series forecasting, we move on to sequenc...

torch time series, final episode: Attention

We conclude our mini-series on time-series forecasting with torch by augmenting ...

sparklyr 1.6: weighted quantile summaries, power iterat...

The sparklyr 1.6 release introduces weighted quantile summaries, an R interface ...

torch for optimization

Torch is not just for deep learning. Its L-BFGS optimizer, complete with Strong-...

Que haja luz: More light for torch!

Today, we're introducing luz, a high-level interface to torch that lets you trai...

Introducing mall for R...and Python

We are proud to introduce the {mall} package. With {mall}, you can use a local ...

sparklyr.sedona: A sparklyr extension for analyzing geo...

We are excited to announce the availability of sparklyr.sedona, a sparklyr exten...

Starting to think about AI Fairness

The topic of AI fairness metrics is as important to society as it is confusing. ...

torch: Just-in-time compilation (JIT) for R-less model ...

Using the torch just-in-time (JIT) compiler, it is possible to query a model tra...

Beyond alchemy: A first look at geometric deep learning

Geometric deep learning is a "program" that aspires to situate deep learning arc...

Train in R, run on Android: Image segmentation with torch

We train a model for image segmentation in R, using torch together with luz, its...

Revisiting Keras for R

It's been a while since this blog featured content about Keras for R, so you mig...

Pre-processing layers in keras: What they are and how t...

For keras, the last two releases have brought important new functionality, in te...

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