Sep 23–26, 2019
Paco Nathan

Paco Nathan
evil mad scientist, Derwen

Website

Paco Nathan is known as a player/coach, with core expertise in data science, natural language processing, machine learning, and cloud computing. He has 35+ years tech industry experience, ranging from Bell Labs to early-stage startups. He’s co-chair for Rev conf, former co-chair for JupyterCon. Advisor for NYU Coleridge Initiative, IBM Data Science Community, Amplify Partners, Recognai, Primer AI, and Data Spartan. Cited in 2015 as one of the Top 30 People in Big Data and Analytics by Innovation Enterprise. Co-author of the upcoming Rich Search and Discovery for Research Datasets.

Sessions

11:20am12:00pm Wednesday, September 25, 2019
Location: 1A 08/10
Secondary topics:  Culture and Organization
Ann Spencer (Domino), Paco Nathan (Derwen), Amy Heineike (Primer), Pete Warden (TensorFlow)
If, as a data scientist, you've wondered why it takes so long to deploy your model into production or, as an engineer, thought data scientists have no idea what they want, you're not alone. Join a lively discussion panel with industry veterans Ann Spencer, Paco Nathan, Amy Heineike, and Pete Warden to find best practices or insights on increasing collaboration when developing and deploying models. Read more.

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