Machine Learning Engineering and Optimization for Improving Seafood Production

In this project, machine learning and optimization will be applied to a 20 GB dataset on raw fish quality and process control parameters collected by the Tally software over a three-year period in a large industrial tuna cannery processor. The goal of the research is to design predictive machine learning and optimization algorithms maximizing the production yields and reducing waste, which could save hundreds of thousands or even millions of dollars a year depending on the seafood processor scale. The partner organization, ThisFish Inc.