General Training Session: Fake News Detection with Machine Learning (ML) and Natural Language Processing (NLP)

Abstract: Natural language processing is considered to be one of the most challenging part of Machine Learning. Importance of understanding the given text includes but not limited to sentiment analysis, information extraction, summarization. IN this training session, we will try to tackle one of the most important problem, Misinformation Detection.

The rising issue of fake news news has been widely studied recently. Its impact on politics, marketing ads etc. undeniable big and it is a very hard problem to solve. In this training session, we will learn about importance of the data, how to select the right data for the given problem, machine learning techniques, mainly focus on supervised classification methods, natural language processing, modeling, validation and some algorithms to grid search to tune your model.

Bio: Yunus Genes is completing his Masters in Computer Science, and continuing his part time PhD at University of Central Florida. His research is focused on Applied Machine Learning, social media behavior, misinformation detection/diffusion. He has been working on this field over 4 years. His is currently working on a DARPA funded project to simulate social media under SocialSim project, teaching Data Science to Fortune 50 Company professionals and he has previously held Data Science positon at Silicon Valley as well as Florida, Orlando area.