Search Results for "tasks"

...The package emphasizes reproducibility and privacy by enabling local execution of models, which is especially valuable for sensitive or research-oriented workflows. It supports common LLM tasks such as text generation, annotation, and embedding creation, making it useful for tasks like document analysis and data labeling. The design mirrors familiar R workflows, allowing users to integrate AI capabilities into scripts, notebooks, and data pipelines with minimal friction. It also provides flexibility to extend functionality to any feature supported by the underlying Ollama API.

devtools is an R package designed to simplify R package development by providing functions for creating, building, testing, and installing packages from various sources (e.g., CRAN, GitHub). It integrates with usethis, roxygen2, testthat, and simplifies workflows for developers and contributors to the R ecosystem.

This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. ...