Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Amit Kapoor

Amit Kapoor
Data Storyteller, narrativeVIZ Consulting

Website | @amitkaps

Amit Kapoor is interested in learning and teaching the craft of telling visual stories with data. At narrativeVIZ Consulting, Amit uses storytelling and data visualization as tools for improving communication, persuasion, and leadership through workshops and trainings conducted for corporations, nonprofits, colleges, and individuals. Amit also teaches storytelling with data as guest faculty in executive courses at IIM Bangalore and IIM Ahmedabad. Amit’s background is in strategy consulting, using data-driven stories to drive change across organizations and businesses. He has more than 12 years of management consulting experience with AT Kearney in India, Booz & Company in Europe, and more recently for startups in Bangalore. Amit holds a BTech in mechanical engineering from IIT, Delhi, and a PGDM (MBA) from IIM, Ahmedabad. Find more about him at Amitkaps.com.

Sessions

16:3517:15 Wednesday, 23 May 2018
Data science and machine learning, Visualization and user experience
Location: Capital Suite 14 Level: Beginner
Secondary topics:  Visualization, Design, and UX
Bargava Subramanian (Impel Labs), Amit Kapoor (narrativeVIZ Consulting)
Creating visualizations for data science requires an interactive setup that works at scale. Bargava Subramanian and Amit Kapoor explore the key architectural design considerations for such a system and discuss the four key trade-offs in this design space: rendering for data scale, computation for interaction speed, adapting to data complexity, and being responsive to data velocity. Read more.
16:3517:15 Thursday, 24 May 2018
Data science and machine learning, Visualization and user experience
Location: Capital Suite 13 Level: Intermediate
Amit Kapoor (narrativeVIZ Consulting), Bargava Subramanian (Impel Labs)
Amit Kapoor and Bargava Subramanian lead three live demos of deep learning (DL) done in the browser—building explorable explanations to aid insight, building model inference applications, and rapid prototyping and training an ML model—using the emerging client-side JavaScript libraries for DL. Read more.