[Live Webinar] Taking the edge off of data science with dabl

## Here is the link to join the webinar:
https://www.bigmarker.com/neo4j/Data-Umbrella-Webinar

## Time
9am PDT / 12pm EDT / 7pm EAT / 9:30 PM IST

## Talk Level
Intermediate

## Pre-reqs
Some familiarity with pandas, matplotlib and scikit-learn

## Prep Work
None

## Resources
https://dabl.github.io

## Event
In many real-world applications, data quality and curation and domain knowledge play a much larger role in building successful models than coming up with complex processing techniques and tweaking hyper-parameters.

Therefore, a data toolbox should enable users to understand both data and model, and not burden the practitioner with details of formatting plots, rote preprocessing steps and hyperparameters.

The dabl library is a first step in this direction. It provides automatic visualization routines and model inspection capabilities while automating away model selection.
This talk will introduce the dabl library and show how to use it to quickly create supervised models and identify modeling and data quality issues.

## Speaker
Andreas Müller is a Principal Research SDE at Microsoft, where he works on the interface of the Data Science ecosystem and cloud infrastructure. He previously held positions as Associate Research Scientist at the Columbia Data Science Institute and as a Research Engineer at the NYU Center for Data Science. He is one of the core developers of the scikit-learn machine learning library, a member of the scikit-learn technical committee, and the author of the book "Introduction to machine learning with Python". His work focuses on practical aspects of machine learning and the development of user-centric machine learning software.

Linkedin: https://www.linkedin.com/in/andreas-mueller-b370265a/
Twitter:https://twitter.com/amuellerml
GitHub: https://twitter.com/amueller