Deepfake detection challenge

A couple of months ago, Amazon, Facebook, Microsoft, and other contributors initiated a challenge consisting of telling apart real and AI-generated (“fake”) videos. We show how to approach this challenge from R.

State-of-the-art NLP models

Nowadays, Microsoft, Google, Facebook, and OpenAI are sharing lots of state-of-the-art models in the field of Natural Language Processing. However, fewer materials exist how to use these models from R. In this post, we will show how R users can access and benefit from these models as well.

Bidirectional Encoder Representations from Transformers

A deep learning model - BERT from Google AI Research - has yielded state-of-the-art results in a wide variety of Natural Language Processing (NLP) tasks. In this tutorial, we will show how to load and train the BERT model from R, using Keras.

COVID-19 dashboard

This dashboard for COVID-19 visualization utilizes Prophet, a forecasting library, with Bayesian optimization to accurately predict future cases. It provides an intuitive interface for users to explore real-time and historical data.

fastai: Empowering R with Fast.ai Functionality for Deep Learning

The fastai library simplifies training fast and accurate neural nets using modern best practices. See the fastai website to get started. The library is based on research into deep learning best practices undertaken at fast.ai and includes "out of the box" support for vision, text, tabular, etc.