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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