Introduction to Machine Learning
Machine learning continues to be a hot topic for organizations looking to get more accuracy from their analytic models. But there are several practical issues that should be considered in applying it to real-world industry problems.
In this this webinar, Wayne Thompson of SAS delves into those issues and provides an overview of machine learning, as well as key business applications of this technique, including fraud detection, model factories and recommendation systems.
- Learn about four focus areas of machine learning: unsupervised learning, supervised learning, semisupervised learning and reinforcement learning.
- Get useful tips on feature engineering, ensemble modeling, bias variance, shrinkage and model evaluation.
- Get insight into the future of machine learning, including cognitive computing and robot learning.