Numerical Algorithms Group (NAG)

pybobyqa

Python-based Derivative-Free Optimization with Bound Constraints

NAGPythonExamples

Examples and demos showing how to call functions from the NAG Library for Python

LAPACK_Examples

Example programs showing how to call LAPACK driver and computational routines (Fortran double precision)

dfols

Python-based Derivative-Free Optimizer for Least-Squares

dfogn

DFO-GN: Derivative-Free Optimization using Gauss-Newton

implied-vol

nagcpp

C++ Interfaces for the NAG Library

2decomp_fft

pypop

Python Tools for the POP Metrics

Ski-LLS

HighPerformancePythonTraining

NAGPythonLibraryTraining

Hands on exercises and solutions for training in the NAG Library for Python

dfbgn

Python solver for large-scale nonlinear least-squares minimization without derivatives

AlgorithmicDifferentiation

NAGJavaExamples

Examples demonstrating the NAG Numerical Library for Java

robinhood-reports

A set of reports for presenting data collected by the Robinhood Policy Engine

AzureML_Best_Practice

Reference Implementations of AzureML Workloads with Cost/Performance Best Practice

dco_cpp

mongodb

changepoint analysis for stock prices

bayesian-uq

MLFirstSteps_Azure

Tutorial demonstrating how to get started porting an existing Machine Learning application to MS Azure

UCL-Talk-20160311

Talk materials

ExcelTraining

Training course on calling the NAG Fortran Library (Mark 25) from Microsoft Excel (2013)

kdb_ffi

NAGPython_PyQ

Using the NAG Library for Python with Kdb+ and PyQ

performance_profiling_examples

Accompanying resources for the NAG webinar and blog series

spack

A flexible package manager that supports multiple versions, configurations, platforms, and compilers.

The-Role-of-Matrix-Functions

A Jupyter Notebook about using matrix functions with the NAG Library for Python

gitlab-mirror-and-ci-action

Github action which manually mirrors a repository to Gitlab and keeps track of Gitlab's CI/CD pipelines.