In this episode of Hallway Conversations, we sit down to discuss the concepts and theory behind Machine Learning with Seth Juarez of DevExpress. Seth takes us through understanding the concepts and complexities of Machine Learning, explaining both the underlying principles and the types of problems for which Machine Learning is well-suited (as well as not well-suited!). We discuss the techniques for applying Machine Learning to many problem domains and explore different techniques for handling data as input to systems based on Machine Learning algorithms.
Seth also digs into the concepts behind his NuML library for Machine Learning on the .NET platform and explains how you can leverage this powerful technique in your daily programming projects to improve the mechanisms your software uses to discriminate and make important decisions based on input data. We also talk about the new Azure Machine Learning services (that have just been announced in Developer Preview) and discuss how you can use this powerful capability to enhance your own software, whether on-premises or in the cloud.
Lastly, we talk a bit about whether Machine Learning is really the first step to Artificial Intelligence or whether we’re just building ever-faster automatons that merely approximate the appearance of intelligence, despite being still quite stupid at their core; along the way, we’ll dig into Neural Networks and do some Deep Thinking too!
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, NuML.NET, intended to simplify the use of popular machine learning models, as well as complex statistics and linear algebra.