Please allow me to introduce myself: Torch for R
Today, we are excited to introduce torch, an R package that allows you to use PyTorch-like functionality natively from R. No Python installation is re…
Category: Uncategorized
Introducing sparklyr.flint: A time-series extension for sparklyr
We are pleased to announce that sparklyr.flint, a sparklyr extension for analyzing time series at scale with Flint, is now available on CRAN. Flint is…
An introduction to weather forecasting with deep learning
A few weeks ago, we showed how to forecast chaotic dynamical systems with deep learning, augmented by a custom constraint derived from domain-specific…
Training ImageNet with R
This post explores how to train large datasets with TensorFlow and R. Specifically, we present how to download and repartition ImageNet, followed by t…
Deepfake detection challenge from R
A couple of months ago, Amazon, Facebook, Microsoft, and other contributors initiated a challenge consisting of telling apart real and AI-generated ("…
FNN-VAE for noisy time series forecasting
In the last part of this mini-series on forecasting with false nearest neighbors (FNN) loss, we replace the LSTM autoencoder from the previous post by…
State-of-the-art NLP models from R
Nowadays, Microsoft, Google, Facebook, and OpenAI are sharing lots of state-of-the-art models in the field of Natural Language Processing. However, fe…
Parallelized sampling using exponential variates
How can the seemingly iterative process of weighted sampling without replacement be transformed into something highly parallelizable? Turns out a well…
Time series prediction with FNN-LSTM
In a recent post, we showed how an LSTM autoencoder, regularized by false nearest neighbors (FNN) loss, can be used to reconstruct the attractor of a …
sparklyr 1.3: Higher-order Functions, Avro and Custom Serializers
Sparklyr 1.3 is now available, featuring exciting new functionalities such as integration of Spark higher-order functions and data import/export in Av…
