Detecting IoT Network Intrusion With Plotly

Build an intrusion detection app with Plotly's Dash tool and the DataScience.com Platform to assess whether an IoT network has been compromised.

April 25, 2018 | 10:30 - 11:30 a.m. PST

About the webinar

DataScience.com has partnered with Plotly to enable our customers to easily leverage the company's leading open source tools for composing, editing, and sharing interactive data visualizations via the Web, as well as its new pythonic framework, Dash. 

In this live webinar, DataScience.com Lead Data Scientist Jean-René Gauthier and Plotly Cofounder and Dash Author Chris Parmer will demonstrate how to build an application that can detect and automatically notify IT and business stakeholders of possible network intrusions at an IoT company. Applications like this one are important to data-driven organizations because they make cross-functional communication of the results of data science work so easy. 

  • Date: Wednesday, April 25, 2018

  • Time: 10:30 - 11:30 a.m. PST

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Chris Parmer
Cofounder, Plotly

Chris Parmer is a cofounder of Plotly and most recently the author of Dash. Chris studied electrical engineering and math at McGill. In 2013, Chris joined Alex Johnson and Jack Parmer in creating one of the web’s first scientific graphing libraries, a project which would become the open source library plotly.js. At Plotly, Chris has led development on Plotly.py (a Python interface to plotly.js), Chart Studio (an interactive chart creation and design tool), Falcon SQL Client (an open source SQL exploration and visualization tool), Dash (a web interface library for Python), among many other projects.

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Jean-René Gauthier
Lead Data Scientist, DataScience.com

Jean-René Gauthier, Lead Data Scientist at DataScience.com, manages a team of data experts in developing algorithms and analytics models to solve customers' unique business problems. He is also responsible for educating clients on these algorithms and models, ensuring that they are incorporated into the business to add maximum value. Prior to his three years at DataScience.com, Jean-René was a data scientist at AuriQ Systems where he focused on online marketing analytics and data engineering, often involving high-speed processing of massive data sets. He has a PhD in astrophysics from the University of Chicago and was a postdoctoral fellow at the California Institute of Technology.