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supplychainanalytics

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In this study, we aimed to detect fraudulent activities in the supply chain through the use of neural networks. The study focused on building two machine learning models using the MLPClassifier algorithm from the scikit-learn library and a custom neural network using the Keras library in Python.

  • Updated Jul 29, 2024
  • Jupyter Notebook

A supply chain analytics project to optimise the transportation of perishable raw materials from production facilities in mainland Europe to processing plants in the UK, and thereafter to storage and distribution centres across UK.

  • Updated Nov 22, 2021
  • R

This repository contains the links for different posts on application of open source programming languages in operation research and supply chain management.

  • Updated Jan 9, 2022

A comprehensive project delved into the data analysis of various functions of a Hardware manufacturing company like Finance, Sales, Marketing & Supply Chain which will help to generate insights and make data driven decisions in these departments.

  • Updated Sep 14, 2024

This repository contains my analysis for the FP20 Analytics Challenge (Feb 2025) on Transportation & Logistics Analysis. In this Power BI File I find out the Top Shipping Routes, Delay Timelines & Patterns, Key Suppliers & Their Performance, Top Customers & Their Order Distribution.

  • Updated Mar 13, 2025
  • Jupyter Notebook

Analyzing logistics data to optimize shipment efficiency, reduce delays, and enhance supply chain visibility using Power BI. Insights include top routes, delays, supplier trends, and peak shipments.

  • Updated Apr 10, 2025
  • Jupyter Notebook

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