Practical Machine Learning – Recommender Engine and Anomaly Detection


Machine learning is often perceived to be a daunting topic, when in fact its concepts are fairly intuitive and easy to use. This session will introduce nuML machine learning library basics, and will thus address the clustering issue in .NET applications by focusing on the practical real-world applications of recommendation engines and anomaly detection. At the conclusion of this session, attendees will be able to immediately use their unlabeled data to create powerful models for predicting the future based on the past.

Seth Juarez

Seth Juarez holds a Master’s Degree in Computer Science where his field of research was Artificial Intelligence, specifically in the realm of Machine Learning. Seth is the Analytics Program Manager for DevExpress where he specializes in products dealing with data analysis, shaping, and presentation. When he is not working in that area, Seth devotes his time to an open source Machine Learning Library, specifically for .NET, intended to simplify the use of popular machine learning models, as well as complex statistics and linear algebra.