CRUNCH is a use case heavy conference for people interested in building the finest data driven businesses. No matter the size of your venture or your job description you will find exactly what you need on the two-track CRUNCH conference. A data engineering and a data analytics track will serve diverse business needs and levels of expertise.
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Beyond Interactive: Empowering Everyone with Jupyter Notebooks – Michelle Ufford | Crunch 2019

Toward Human-Centered Machine Learning – Patrick Hall | Crunch 2019

Dagster: An open source Python library for building data applications – Nicholas Schrock | Crunch 19

Stories Beat Statistics: Master the Art & Science of Data Storytelling – Brent Dykes | Crunch 2019

Journey of metadata at LinkedIn – Shirshanka Das | Crunch 2019

How to Get the Most Out of Your BI Tools – Keshia Rose | Crunch 2019

The data scientist's hierarchy of needs – Benn Stancil | Crunch 2019

The algorithm for precision medicine – Matt Might | Crunch 2019

Data as culture as software – Andrea Burbank | Crunch 2019

Transfer Learning for Cold Start Problem – Sergey Rubtsovenko | Crunch 2019

Clear and Presentation Danger – Andy Cotgreave | Crunch 2019

Using adversarial samples to robustify your Neural Network Models – Irina Vidal | Crunch 2019

Data Lineage with Apache Airflow using Marquez – Willy Lulciuc | Crunch 2019

Recreating the State of the Player – Wesley Kerr | Crunch 2019

Building low latency gradient boosted tree predictors on distributed platform- György Móra |Crunch19
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