Curious about what human-in-the-loop machine learning actually looks like? Join CrowdFlower and learn how to effectively incorporate Active Learning, Transfer Learning, and Annotation Quality in your ML projects to achieve better results. Join us in this latest Data Science Central webinar, where we will cover the following topics: When to use the human-in-the-loop as an effective strategy for machine learning projects How to set up an effective interface to get the most out of human intelligence How to ensure high-quality, accurate training data sets How to use ML models from different domains to improve your own labeling This webinar will include an end-to-end look at setting up and running a job that generates high-quality training data, and shows how to incorporate that training data into human-in-the-loop machine learning systems that you can run in your own environment.