Get to Know Human in the Loop (HITL)
In order to increase the size, completeness, or accuracy of supervised machine learning datasets you need humans in the loop (HITL). But what is a human in the loop workforce? And why is it important to deep learning and data operations strategies?
Keith McCormick has over two decades of traditional machine learning experience and joined CloudFactory a year ago. Recent interviews with several experts in AI, automation, and decision management illustrated that data labeling techniques and exception processing workforce strategies aren’t common knowledge. In this webinar, Keith shares what he learned about the benefits and meaning of human in the loop, and why this workforce strategy is important to advancements in deep learning.
Watch this webinar to learn more about:
- The rise of deep learning and misconceptions about how computers learn
- The role humans in the loop play beyond labeling training datasets, such as real-time exception processing
- Why many data scientists don’t understand human in the loop
- How human in the loop is driving rapid progress in insurance, agriculture, retail, fitness, autonomous vehicles, and business intelligence
Follow CloudFactory on LinkedIn for notifications about our upcoming webinars.
Keith McCormick is an independent data miner, trainer, conference speaker, and author. He serves as CloudFactory’s Chief Data Science Advisor. Over 25 years, he has guided data science teams to establish highly effective analytical practices across industries, including the public sector, media, marketing, healthcare, retail, finance, manufacturing, and higher education.