Engineering Machine Learning Applications
14th November, 14:00-15:00
You are a software engineer and would like to get into machine learning. Instead of starting with traditional approach that begins with theory, math, probability, algebra, this talk will address what does it take build a solution. We’ll discuss the process of building a machine-learning application, how to specify requirements, what is the development process, what are the best-of-breed tools and platforms, how to design tests, and how to do maintenance. As in software development, only a systematic process can lead to achieving high-quality results repeatable from project to project.
Boštjan Kaluža, PhD is the Chief Data Scientist at Evolven. He's done a lot of research into artificial intelligence and intelligent systems, machine learning, predictive analytics and anomaly detection. Prior to Evolven, Boštjan served as a senior researcher in the Department of Intelligent Systems at the Jozef Stefan Institute, the leading Slovenian scientific research institution and led research projects involving pattern and anomaly detection, machine learning and predictive analytics. Focusing on the detection of suspicious behavior and data analysis, Boštjan has published numerous articles in professional journals and delivered conference papers. Boštjan published two books on data science, Instant Weka How-to, exploring how to leverage machine learning using Weka, and Machine Learning in Java, for learning how to use Java's machine learning libraries to gain insight from data. Boštjan is also the author and contributor to a number of patents in the areas of anomaly detection and pattern recognition.