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Using Machine Learning to Optimize COVID-19 Predictions
With the current COVID-19 pandemic impacting many aspects of our lives, understanding the data and models around COVID-19 data are ever more crucial. Understanding the potential number of cases impacts the guidance around our policies (needing more hospital ICU beds, when to ease stay at home orders, when to open schools, etc.).
With the current COVID-19 pandemic impacting many aspects of our lives, understanding the data and models around COVID-19 data are ever more crucial. Understanding the potential number of cases impacts the guidance around our policies (needing more hospital ICU beds, when to ease stay at home orders, when to open schools, etc.).
Using Machine Learning to Optimize COVID-19 Predictions
1.
Improving IHME Covid Model
Scott Black, Solution Architect, Databricks
Denny Lee, Staff Developer Advocate, Databricks
2.
Agenda
Building a Unified COVID-19 Data
Lake
Denny Lee
Improving IHME COVID-19
Predictions
Scott Black
3.
Scott Black
Solution Architect at Databricks
▪ 10 Years Helping Organizations
Getting Value From Their Data
▪ Deep RDBMS Experience In
E-Commerce & Healthcare
▪ Contributed to Several Oracle
Books
4.
Denny Lee
Staff Developer Advocate at
Databricks
Previously
▪ Senior Director of Data Science
Engineering at Concur
▪ Principal Program Manager at at
Microsoft
▪ Project Isotope (Azure HDInsight)
▪ SQLCAT DW/BI Lead
7.
Feedback
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8.
Improving IHME Predictions
▪ Evaluate IHME Model Performance
▪ Compare Multiple Versions Of IHME Models To Visualization Their Performance
▪ Combine Predictions With Actual Outcomes
▪ Are New Version Improving
▪ Improve IHME Predictions
▪ Taking Actual Model Performance Attempt To Provide Better Prediction