A Python-embedded modeling language for convex optimization problems.
AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.
OptaPlanner quick starts for AI optimization: many use cases shown in many different technologies.
A next-gen Lagrange-Newton solver for nonconvex constrained optimization. Unifies barrier and SQP methods in a generic way, and implements various globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
Formulate trained predictors in Gurobi models
Derivative-Free Global Optimization Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP
Investment Funnel 📈 is an open-source python platform designed for an easy development and backtesting of outperforming investment strategies.
Neuromorphic mathematical optimization with Lava
Deep Learning Specialization course offered by DeepLearning.AI on Coursera
Fortran bindings for the NLopt library
This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI
Distances to sets for MathOptInterface
Pure Python solver for the multi-way partition problem
Two-Stage Robust Rostering Problem from the nested C&CG paper
Nonlinear programming application examples solved with Artelys Knitro
A simple implementation of the Benders decomposition method with JuMP
SemiDefinite Programming Algorithm (SDPA) for Python
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