Systems | Development | Analytics | API | Testing

Appian Workforce Safety now offers Vaccination Insights, a flexible, user-friendly, compliant solution to track vaccine status by individual, location, time frame, and more. Employers can determine what specific questions are asked of their employees in the easy-to-use interface.

Data driven healthcare, anonymized data hackathons in a digital data sandbox, how to leverage the power of data for good, compute on demand, how the pandemic has affected digital adoption and how shifting to the cloud impacts patients are just some of the topics being covered in today's episode of Snowflake's Rise of the Data Cloud. Join us as Ashok Chennuru, Chief Data and Analytics Officer at Anthem gives us a peek into the world of AI and healthcare.

In this webinar, we will talk about enterprise scale, fully automated MLOps solutions for Trade Promotions, looking into the impact this can create for CPG companies, through a real-world example.

Many enterprises today face numerous challenges around handling data for AI/ML. They find themselves having to manually extract datasets from a variety of sources, which wastes time and resources. In this session, we discuss end-to-end automation of the production pipeline and how to govern AI in an automated way. We touch upon setting up a feedback loop, generating explainable AI and doing all of this — at scale.

We discuss how enterprises need a platform that brings together tools to streamline data science workflow with leading edge infrastructure that can tackle the most complex ML models — one that can bring innovative concepts into production sooner, integrated within your existing IT/DevOps-grounded approach.

We discuss some common applications for machine learning at the edge and the main challenges associated with deploying distributed cloud and edge applications. We then wrap up the session with a live demo showing how to run a distributed cloud or edge application on Amazon Cloud and Outposts with the Iguazio Data Science Platform.

The breakdown:

00:00 - Intro
02:15 - MLOps Overview
05:03 - Feature Engineering
07:44 - MLOps Workflow
10:44 - Solution: Feature Store
14:25 - Feature Store Competitive Landscape
17:03 - Features of a Feature Store
21:01 - CTO: Feature Store Sneakpeak
25:55 - Python Code example
27:57 - ML Pipeline example
30:07 - Covid-19 Patient Deterioration
33:26 - LIVE DEMO
52:45 - QA