Getting Started with Machine Learning
Using system thinking principles to guide your machine learning experiments allows you to maintain a deeper understanding of the elements that influence intelligent systems and will aid in avoiding the common pitfalls of machine learning projects.
Join me on O’Reilly’s Online Learning platform, Safari, for a hands-on introduction to machine learning. You’ll explore scalable project workflows and common pitfalls and walk through the steps for developing and deploying production-ready machine learning solutions. Throughout the course, I will incorporate systems thinking principles as a foundation for improving algorithmic performance, providing a deeper understanding of the assumptions and elements (systems) that will influence (train) your models. This hybrid approach integrating machine learning with systems thinking improves a project’s effectiveness and ultimately supports the goal of developing machine learning solutions that make a positive impact in the areas that matter.
Using Systems Thinking & Machine Learning to Uncover the Power of Time
During the course, I will demonstrate purposeful machine learning using a sample time-use dataset. Time-use datasets include snapshots or summaries of how a person spends or allocates their time. We will explore how data can uncover patterns of behavior using a real-world dataset containing both unstructured and structured data. To begin, we will start with a training set of approximately 120K work day summaries (reflects approx. 1000 unique people).
For course details and to register for the course, please visit https://www.safaribooksonline.com/live-training/courses/getting-started-with-machine-learning/0636920174691/