Search Results for "fb2k-component"

...It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica (Independent Component Analysis) and pca (Principal Component Analysis) transformations, respectively, concatenated with the hot-bit encoding (ohe) of categorical features (catf) of a given data for rf (Random Forest) modeling.

A Julia package for multivariate statistics and data analysis (e.g. dimensionality reduction).

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

Welcome to the documentation for Starlight.jl, a greedy application framework for greedy developers. Its primary use case is video games, but the power of Julia, SDL2, Vulkan, and the Bullet Physics SDK can be leveraged to make just about anything you want. With a focus on flexibility and code quality, Starlight aims to be such a framework. It includes a suite of components and integrations that make it particuarly well-suited for video games, so it is not a stretch to call it a "game...

...For this purpose, a topology optimization method is being developed which takes into account the unique material properties of parts manufactured with the SLM-process. In this homepage, the generation of a material database as well as the development of the topology optimization method is introduced and the impact on the component design is presented. SLM-Topo is a joint research project of the Institute of Product Engineering (IPEK) and the Institute for Applied Materials (IAM) of the Karlsruhe Institute for Technology (KIT) funded by the Deutsche Forschungsgemeinschaft (DFG).