Tag: logistics

Demand Clustering and Segmentation with Machine Learning in Logistics (Kmeans, scikit-learn, matplotlib)

Demand Clustering and Segmentation with Machine Learning in Logistics (Kmeans, scikit-learn, matplotlib) In the field of logistics, understanding and predicting customer demand patterns is crucial for optimizing supply chain operations. By employing machine learning techniques, we can cluster and segment demand data to uncover valuable insights and make informed decisions. In this tutorial, we will explore how to perform demand clustering and segmentation using Python and popular machine learning libraries. Prereqs To follow along with this tutorial, you’ll need: Python…

Predicting Delivery Time and Estimating Shipment Delays with Machine Learning (Supply Chain and Logistics Series)

Predicting Delivery Time and Estimating Shipment Delays with Machine Learning (Supply Chain and Logistics Series) In today’s fast-paced world, efficient delivery and logistics are crucial for businesses. Predicting delivery times accurately and estimating shipment delays can help companies streamline their operations, optimize resources, and provide better customer service. Machine learning techniques can be employed to analyze historical data and build predictive models that can forecast delivery times and identify potential delays. In this tutorial, we will explore how to use…