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  • šŸ‘‹ Hi, Iā€™m @ZedTDean
  • šŸ‘€ Iā€™m interested in ...Operational Research / Optimisation / Simulation
  • šŸŒ± Iā€™m in love with ...Gurobi API/ AMPL / Python / R / SAS / C++ / C# / Dockerfile /Docker Compose / Kubernetes / Powershell
  • šŸ’žļø Iā€™m looking to collaborate on ...Mathematical Programming, Discrete Event Simulation, System Dynamics, Data Envelopment analysis
  • šŸ“« How to reach me [email protected]

Zed Dean's Projects

bonmin icon bonmin

Basic Open-source Nonlinear Mixed INteger programming

coin-or-optimizationsuite icon coin-or-optimizationsuite

A harness for building the bundled suite of interoperable optimization tools available in the COIN-OR repository.

docker-manager icon docker-manager

The gurobi/manager image provides a Docker image ready to be deployed as a Cluster Manager.

docker-modeling-examples icon docker-modeling-examples

The gurobi/modeling-example image includes a Jupyter Notebook that allows you to browse and execute any of the Python modeling examples.

docker-optimizer icon docker-optimizer

The gurobi/optimizer image provides a base Docker image for building applications using any of the supported APIs (C, C++, Java, .NET, Python, MATLAB, and R), as well as the command line tools such as gurobi_cl and the Python shell. If you are planning to only use the Python API, we recommend using the gurobi/python image instead.

grblogtools icon grblogtools

Extract and visualize information from Gurobi log files

gurobipy-pandas icon gurobipy-pandas

Convenience wrapper for building optimization models from pandas data

handson-ml3 icon handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

ml-foundations icon ml-foundations

Machine Learning Foundations: Algebra, Calculus, Statistics & Computer Science

pydea icon pydea

Data envelopment analysis module for python.

relu_ann_milp icon relu_ann_milp

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.

sas-global-forum-2020 icon sas-global-forum-2020

Code and examples that accompany papers and presentations from SAS Global Forum 2020 (Mar 29 - Apr 1 in Washington, DC)

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