Machine learning [EN] Archives

Simulation, Scheduling, Optimization, ERP

Machine learning and discrete-event simulation

In this article I discuss machine learning and discrete-event simulation. I will introduce machine learning as a supportive technology for making discrete-event simulation more resource efficient and effective. Discrete-event simulation is a technique used in manufacturing and logistics for problems […]

Support vector machine with Gekko in Python

In this blog post I model a support vector machine in Python. Previously, I modeled and solved the quadratic assignment problem (QAP) in Python using Pyomo (+). I described that the “similarity” of two facilities could be a reason for […]

Gekko for linear demand pricing

How can we decide on a product or service price using observed data over time? For example, a retailer may have changed the price for a specific product in multiple time slots of a week, tested the demanded quantity (sales) […]

Three basic paradigms of machine learning

In previous posts, we have introduced exemplary machine learning algorithms for common real-world problems. We e.g. introduced optimization for shallow learning and deep learning models. In this article, we want to clarify the three main paradigms of machine learning. These […]

Shallow and deep supervised learning model

In this post, I explain how supervised learning models in machine learning use single or multiple neurons in a single layer (shallow learning) or multiple neurons in multiple layers (deep learning) to generate a real, binary, or integer value beneficial […]

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Machine learning [EN]

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