A Python-embedded modeling language for convex optimization problems.
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Updated
Sep 27, 2024 - C++
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.
Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).
OptaPlanner quick starts for AI optimization: many use cases shown in many different technologies.
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.
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.
A next-gen solver for optimization with nonconvex objective and constraints. Unifies barrier and SQP methods in a modern and generic way, and unlocks a variety of novel methods. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
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
Distances to sets for MathOptInterface
This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI
Pure Python solver for the multi-way partition problem
Two-Stage Robust Rostering Problem from the nested C&CG paper
A simple implementation of the Benders decomposition method with JuMP
Implementation of different techniques to solve the Set Covering Problem (SCP).
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