![]() Key features of the dataset - Fast-Food Chains, U.S. I added this project to my resume when I graduated and it helped me get my first job at Pactera!Ĭlassify the mobile price range for an interesting case study. Selected datasets for free download, have fun, and don’t forget to leverage them into your Portfolio!Īnonymized credit card transactions are labeled as fraudulent or genuine. I share my learning journey into Data Science with my amazing LinkedIn friends, click follow and let's grow together! Alex Wang #artificialintelligence #machinelearning #datascience #algorithms To solve it, we can try to apply a modification of the Self-Organizing Map (SOM) technique. Check this repo: īy Diego Vicente, read more in the comments.Ĭheck if your ML models have not silently failed after deployment:įor more ML/ AI/ Data Science learning materials, please check my previous posts. The difficulty to solve it increases rapidly with the number of cities, and we do not know in fact a general solution that solves the problem.įor that reason, we currently consider that any method able to find a sub-optimal solution is generally good enough (we cannot verify if the solution returned is the optimal one most of the time). It consists of finding the shortest route possible that traverses all cities on a given map only once. ![]() The Problem is a well-known challenge in Computer Science: Solving the Traveling Salesman Problem using Self-Organizing Maps. ![]()
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