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mall 0.2.0

The mall 0.2.0 update for R and Python introduces support for external LLM providers like OpenAI and Gemini. This version also features parallel processing for R users, the ability to run NLP on string vectors in Python, and a brand new cheatsheet

Edgar Ruiz

Aug 19, 2025

Artificial Intelligence Machine Learning Ai LLM Polars Natural Language Processing Tabular Data

video

LLMs for Data Science

[2025 - Day 1 - Data Science & Algos] Hadley Wickham shares insights from practical applications of LLMs in data science, exploring three key areas where these tools prove genuinely useful beyond the hype: writing code, writing prose, and rectangling non-rectangular data. For data scientists working with text, images, videos, or audio data, this talk offers valuable perspectives on leveraging LLMs effectively for real workflows and transforming fundamentally unstructured information.

ABOUT THE SPEAKER: Hadley Wickham, Chief Scientist, Posit

ABOUT DATA COUNCIL: Data Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools.

FIND US: Twitter: https://twitter.com/datacouncilai LinkedIn: https://www.linkedin.com/company/datacouncil-ai/ Website: https://www.datacouncil.ai/

Hadley Wickham

May 29, 2025

23 min

1.5k views

Data Science Tutorial LLM for Data Science AI Tutorial ChatGPT Artificial Intelligence Machine Learning Python Tutorial AI Assistance Coding With AI Automation Productivity Tools Data Analysis Rectangling Data Text Analysis Natural Language Processing Data Preprocessing Feature Engineering Model Building Model Evaluation Statistical Analysis Exploratory Data Analysis Data Visualization Machine Learning Workflows

blog post

Introducing mall for R…and Python

We are proud to introduce the {mall} package. With {mall}, you can use a local LLM to run NLP operations across a data frame. (sentiment, summarization, translation, etc). {mall} has been simultaneously released to CRAN and PyPi (as an extension to Polars)

Edgar Ruiz

Oct 30, 2024

Artificial Intelligence Machine Learning Ai LLM Polars Natural Language Processing Tabular Data

blog post

What are Large Language Models? What are they not?

What are Large Language Models? What are they not?

This is a high-level, introductory article about Large Language Models (LLMs), the core technology that enables the much-en-vogue chatbots as well as other Natural Language Processing (NLP) applications. It is directed at a general audience, possibly with some technical and/or scientific background, but no knowledge is assumed of either deep learning or NLP. Having looked at major model ingredients, training workflow, and mechanics of output generation, we also talk about what these models are not

Sigrid Keydana

Jun 20, 2023

Best Practices Artificial Intelligence Ai Meta Concepts Natural Language Processing

blog post

GPT-2 from scratch with torch

Implementing a language model from scratch is, arguably, the best way to develop an accurate idea of how its engine works. Here, we use torch to code GPT-2, the immediate successor to the original GPT. In the end, you’ll dispose of an R-native model that can make direct use of Hugging Face’s pre-trained GPT-2 model weights

Sigrid Keydana

Jun 20, 2023

Machine Learning Artificial Intelligence Ai Torch Natural Language Processing

blog post

LLaMA in R with Keras and TensorFlow

Implementation and walk-through of LLaMA, a Large Language Model, in R, with TensorFlow and Keras

Tomasz Kalinowski

May 25, 2023

keras3 Machine Learning Artificial Intelligence Ai TensorFlow Keras Generative Models Natural Language Processing

blog post

Introducing the text package

The text package attempts to provide user-friendly access and pipelines to HuggingFace’s transformer language models in R

Oscar Kjell, Salvatore Giorgi, H Andrew Schwartz

Oct 4, 2022

Machine Learning Ai Natural Language Processing

blog post

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, 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

Turgut Abdullayev

Jul 30, 2020

reticulate Machine Learning Ai Natural Language Processing

blog post

Innocent unicorns considered harmful? How to experiment with GPT-2 from R

Innocent unicorns considered harmful? How to experiment with GPT-2 from R

Is society ready to deal with challenges brought about by artificially-generated information - fake images, fake videos, fake text? While this post won’t answer that question, it should help form an opinion on the threat exerted by fake text as of this writing, autumn 2019. We introduce gpt2, an R package that wraps OpenAI’s public implementation of GPT-2, the language model that early this year surprised the NLP community with the unprecedented quality of its creations

Sigrid Keydana, Javier Luraschi

Oct 23, 2019

reticulate Artificial Intelligence Ai Natural Language Processing Packages Releases

blog post

BERT from R

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

Turgut Abdullayev

Sep 30, 2019

keras3 Machine Learning Ai Natural Language Processing TensorFlow Keras

blog post

Attention-based Image Captioning with Keras

Attention-based Image Captioning with Keras

Image captioning is a challenging task at intersection of vision and language. Here, we demonstrate using Keras and eager execution to incorporate an attention mechanism that allows the network to concentrate on image features relevant to the current state of text generation

Sigrid Keydana

Sep 17, 2018

keras3 Machine Learning Ai Natural Language Processing TensorFlow Keras Image Recognition Image Processing

blog post

Attention-based Neural Machine Translation with Keras

Attention-based Neural Machine Translation with Keras

As sequence to sequence prediction tasks get more involved, attention mechanisms have proven helpful. A prominent example is neural machine translation. Following a recent Google Colaboratory notebook, we show how to implement attention in R

Sigrid Keydana

Jul 30, 2018

keras3 Machine Learning Ai Natural Language Processing TensorFlow Keras

blog post

Analyzing rtweet Data with kerasformula

The kerasformula package offers a high-level interface for the R interface to Keras. It’s main interface is the kms function, a regression-style interface to keras_model_sequential that uses formulas and sparse matrices. We use kerasformula to predict how popular tweets will be based on how often the tweet was retweeted and favorited

Pete Mohanty

Jan 24, 2018

keras3 Machine Learning Ai TensorFlow Keras Natural Language Processing

blog post

Classifying Duplicate Questions from Quora with Keras

Classifying Duplicate Questions from Quora with Keras

In this post we will use Keras to classify duplicated questions from Quora. Our implementation is inspired by the Siamese Recurrent Architecture, with modifications to the similarity measure and the embedding layers (the original paper uses pre-trained word vectors)

Daniel Falbel

Jan 9, 2018

keras3 Machine Learning Ai TensorFlow Keras Natural Language Processing

blog post

Word Embeddings with Keras

Word embedding is a method used to map words of a vocabulary to dense vectors of real numbers where semantically similar words are mapped to nearby points. In this example we’ll use Keras to generate word embeddings for the Amazon Fine Foods Reviews dataset

Daniel Falbel

Dec 22, 2017

keras3 Machine Learning Ai TensorFlow Keras Natural Language Processing

blog post

Deep Learning for Text Classification with Keras

Deep Learning for Text Classification with Keras

Two-class classification, or binary classification, may be the most widely applied kind of machine-learning problem. In this excerpt from the book Deep Learning with R, you’ll learn to classify movie reviews as positive or negative, based on the text content of the reviews

François Chollet, J.J. Allaire

Dec 7, 2017

keras3 Machine Learning Ai TensorFlow Keras Natural Language Processing