Data Science Virtual Salon | Retail & E-Commerce

November 17th, 2020
Creatio Accelerate

 November 17th, 2020 - November 18th, 2020 

Data Science Virtual Salon | Retail & E-Commerce

Event submitted on Monday, October 12th 2020, approved by Henry Dalzel

Data Science Virtual Salon | Retail & E-Commerce, November 17th, 2020Click to Tweet

23 Days Until The Event
November 17th, 2020 - November 18th, 2020
United States  »  Northeast, USA  »  New York » 
Event Website

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 Our Review

This would be an excellent conference for those with working with Artificial Intelligence technology and also living and working in New York City

- Review written by Henry Dalziel on Monday, October 12th 2020.
- If you would like to edit or ammend facts in my review please either send us a message or connect with me via LinkedIn.

Event Summary

The following description was either submitted by the Conference Organizer on Monday, October 12th 2020, or created by us.

Data Science Salon unites the brightest leaders in the retail and eCommerce across the nation in data science fields.

The event gathers face-to-face and virtually to educate each other, illuminate best practices, and innovate new solutions. Data Science Salon | Retail & eCommerce is the only industry conference that brings together specialists in the retail and eCommerce data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere.

Get the most current state of current industry trends and innovations in retail and eCommerce through DSS podcasts, exclusive content, Webinars, and Live Training. DSS also has an extensive on-demand video library of presentations from the top industry experts.

Some of the topics that will be discussed:

Personalization at Scale with AI
Cloud Automation and ML
Recommendation Engines
Designing ML pipelines efficiently
Natural Language Processing & Deep Learning
Deep Neural Networks
Image Recognition with ML
Using large scale data sets
Scaling ML Production
Data Science Teams: Managing, Building, Collaboration
Integrating Open Source Tools into your workflows
Improving Data Quality
Machine learning best practices
Data strategy and governance
Data ethics and bias
and More!

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