Dominik Moritz — Building Intuitive Data Visualization Tools

03/25/21 • 39 min

Dominik shares the story and principles behind Vega and Vega-Lite, and explains how visualization and machine learning help each other. --- Dominik is a co-author of Vega-Lite, a high-level visualization grammar for building interactive plots. He's also a professor at the Human-Computer Interaction Institute Institute at Carnegie Mellon University and an ML researcher at Apple. Connect with Dominik Twitter: https://twitter.com/domoritz GitHub: https://github.com/domoritz Personal website: https://www.domoritz.de/ --- 0:00 Sneak peek, intro 1:15 What is Vega-Lite? 5:39 The grammar of graphics 9:00 Using visualizations creatively 11:36 Vega vs Vega-Lite 16:03 ggplot2 and machine learning 18:39 Voyager and the challenges of scale 24:54 Model explainability and visualizations 31:24 Underrated topics: constraints and visualization theory 34:38 The challenge of metrics in deployment 36:54 In between aggregate statistics and individual examples Links Discussed Vega-Lite: https://vega.github.io/vega-lite/ Data analysis and statistics: an expository overview (Tukey and Wilk, 1966): https://dl.acm.org/doi/10.1145/1464291.1464366 Slope chart / slope graph: https://vega.github.io/vega-lite/examples/line_slope.html Voyager: https://github.com/vega/voyager Draco: https://github.com/uwdata/draco Check out the transcription and discover more awesome ML projects: http://wandb.me/gd-domink-moritz --- Get our podcast on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts YouTube: http://wandb.me/youtube Soundcloud: http://wandb.me/soundcloud --- Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices: https://wandb.ai/gallery

Previous Episode

Cade Metz — The Stories Behind the Rise of AI

How Cade got access to the stories behind some of the biggest advancements in AI, and the dynamic playing out between leaders at companies like Google, Microsoft, and Facebook. Cade Metz is a New York Times reporter covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Previously, he was a senior staff writer with Wired magazine and the U.S. editor of The Register, one of Britain’s leading science and technology news sites. His first book, "Genius Makers", tells the stories of the pioneers behind AI. Get the book: http://bit.ly/GeniusMakers Follow Cade on Twitter: https://twitter.com/CadeMetz/ And on Linkedin: https://www.linkedin.com/in/cademetz/ Topics discussed: 0:00 sneak peek, intro 3:25 audience and charachters 7:18 *spoiler alert* AGI 11:01 book ends, but story goes on 17:31 overinflated claims in AI 23:12 Deep Mind, OpenAI, building AGI 29:02 neuroscience and psychology, outsiders 34:35 Early adopters of ML 38:34 WojNet, where is credit due? 42:45 press covering AI 46:38 Aligning technology and need Read the transcript and discover awesome ML projects: http://wandb.me/cade-metz Get our podcast on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts YouTube: http://wandb.me/youtube Soundcloud: http://wandb.me/soundcloud Tune in to our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research: http://wandb.me/salon Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices: https://wandb.ai/gallery

Next Episode

Vladlen Koltun — The Power of Simulation and Abstraction

From legged locomotion to autonomous driving, Vladlen explains how simulation and abstraction help us understand embodied intelligence. --- Vladlen Koltun is the Chief Scientist for Intelligent Systems at Intel, where he leads an international lab of researchers working in machine learning, robotics, computer vision, computational science, and related areas. Connect with Vladlen: Personal website: http://vladlen.info/ LinkedIn: https://www.linkedin.com/in/vladlenkoltun/ --- 0:00 Sneak peek and intro 1:20 "Intelligent Systems" vs "AI" 3:02 Legged locomotion 9:26 The power of simulation 14:32 Privileged learning 18:19 Drone acrobatics 20:19 Using abstraction to transfer simulations to reality 25:35 Sample Factory for reinforcement learning 34:30 What inspired CARLA and what keeps it going 41:43 The challenges of and for robotics Links Discussed Learning quadrupedal locomotion over challenging terrain (Lee et al., 2020): https://robotics.sciencemag.org/content/5/47/eabc5986.abstract Deep Drone Acrobatics (Kaufmann et al., 2020): https://arxiv.org/abs/2006.05768 Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning (Petrenko et al., 2020): https://arxiv.org/abs/2006.11751 CARLA: https://carla.org/ --- Check out the transcription and discover more awesome ML projects: http://wandb.me/vladlen-koltun-podcast Get our podcast on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts YouTube: http://wandb.me/youtube Soundcloud: http://wandb.me/soundcloud --- Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices: https://wandb.ai/gallery