Numerical Algorithms Group (NAG) (@numericalalgorithmsgroup)

Top repositories

1

pybobyqa

Python-based Derivative-Free Optimization with Bound Constraints
Python
78
star
2

NAGPythonExamples

Examples and demos showing how to call functions from the NAG Library for Python
Jupyter Notebook
60
star
3

LAPACK_Examples

Example programs showing how to call LAPACK driver and computational routines (Fortran double precision)
Fortran
60
star
4

dfols

Python-based Derivative-Free Optimizer for Least-Squares
Python
40
star
5

dfogn

DFO-GN: Derivative-Free Optimization using Gauss-Newton
Python
23
star
6

nagcpp

C++ Interfaces for the NAG Library
C++
18
star
7

2decomp_fft

Fortran
17
star
8

pypop

Python Tools for the POP Metrics
Jupyter Notebook
12
star
9

Ski-LLS

C++
9
star
10

dfbgn

Python solver for large-scale nonlinear least-squares minimization without derivatives
Python
8
star
11

HighPerformancePythonTraining

Jupyter Notebook
8
star
12

NAGPythonLibraryTraining

Hands on exercises and solutions for training in the NAG Library for Python
Jupyter Notebook
7
star
13

AlgorithmicDifferentiation

C++
5
star
14

NAGJavaExamples

Examples demonstrating the NAG Numerical Library for Java
Makefile
5
star
15

robinhood-reports

A set of reports for presenting data collected by the Robinhood Policy Engine
PHP
4
star
16

AzureML_Best_Practice

Reference Implementations of AzureML Workloads with Cost/Performance Best Practice
Jupyter Notebook
3
star
17

dco_cpp

C++
3
star
18

MLFirstSteps_Azure

Tutorial demonstrating how to get started porting an existing Machine Learning application to MS Azure
Python
2
star
19

bayesian-uq

C++
2
star
20

NAGPython_PyQ

Using the NAG Library for Python with Kdb+ and PyQ
1
star
21

The-Role-of-Matrix-Functions

A Jupyter Notebook about using matrix functions with the NAG Library for Python
Jupyter Notebook
1
star
22

kdb_ffi

q
1
star
23

performance_profiling_examples

Accompanying resources for the NAG webinar and blog series
1
star