MLBytes Workshop: Using Machine Learning to Prevent the Spread of Mosquito-Borne Diseases
Machine learning seems to be everywhere - across industries and affecting many aspects of daily living. In addition to the more visible chatbot apps, machine learning is being used to predict behaviors and outcomes in industries as varied as healthcare, retail, defense and transportation. These apps are able to sift through huge amounts of data and make sense of it - once they have been "taught" what to look for. This has created demand for data scientists to build algorithms that can find patterns to predict outcomes and behaviors.
Aside from the practical applications of machine learning in business, new solutions are being put into action to help environmental causes that can improve the lives of people and the planet.
Leslie De Jesus will explain how one such solution is being created by Wovenware for the Puerto Rico Science, Technology & Research Trust (PRVCU) which is working to help prevent the spread of mosquito-borne diseases, such as Zika and Dengue Fever, in Puerto Rico and eventually around the world by automating the identification and classification of various species of mosquitoes. The end goal is to use AI to streamline the process through which researchers can uncover insights and correlate specific mosquito populations to environmental conditions, helping them identify and isolate mosquitoes that are resistant to FDA-approved insecticides.