Human-in-the-loop machine learning is all about continuous learning. And as a process, it’s becoming an increasingly common and critical component of emerging technologies. From healthcare analytics and computer vision to autonomous vehicles and natural language processing, human-in-the-loop machine learning is everywhere, but it’s still widely misunderstood. This course is intended to fill those gaps and quickly get you up to speed. Join instructor Keith McCormick as he explores the industry that has arisen to support this challenge, why it’s so important, and how it relates to real-world tasks in data annotation. Discover some of the most common use cases within the larger human-in-the-loop ecosystem. Along the way, Keith shows you how to successfully implement and manage your own data annotation project, including basic skills required for quality control, sampling, active learning, and bias prevention.
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