The Machine Learning from User Interactions (MLUI) workshop seeks to bring together researchers to share their knowledge and build collaborations at the intersection of the Machine Learning and Visualization fields, with a focus on learning from user interaction. Rather than focusing on what visualization can do to support machine learning (as in current Explainable AI research), this workshop seeks contributions on *how machine learning can support visualization*. Such support incorporates human-centric sensemaking processes, user-driven analytical systems, and gaining insight from data. Our intention in this workshop is to generate open discussion about how we currently learn from user interaction, how to build intelligent visualization systems, and how to proceed with future research in this area. We hope to foster discussion regarding systems, interaction models, and interaction techniques. Further, we hope to extend last year’s collaborative creation of a research agenda that explores the future of machine learning with user interaction. We invite research and position papers between 5 and 10 pages in length (NOT including references). All submissions must be formatted according to the VGTC conference template. Papers are to be submitted online through the Precision Conference System at the MLUI track. All papers accepted for presentation at the workshop will be published on IEEE Xplore and linked from the workshop website. These papers are considered archival; reuse of the content in a follow-up publication is only permitted in a proper journal, and any extended version must extend the original paper by at least 30%. Papers will be juried by the organizers and selected external reviewers and will be chosen according to relevance, quality, and likelihood that they will stimulate and contribute to discussion and the workshop. *Submission deadline:* July 15, 2019 *Author notification:* August 6, 2019 *Camera-ready deadline:* August 20, 2019 *Speaker schedule available:* September 15, 2019 *Workshop:* October 20 or 21, 2019 More info and papers from MLUI 2018 can be found at: https://learningfromusersworkshop.github.io/