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Using Machine Learning to Optimize COVID-19 Predictions


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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.).

Published in: Data & Analytics
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Using Machine Learning to Optimize COVID-19 Predictions

  1. 1. Improving IHME Covid Model Scott Black, Solution Architect, Databricks Denny Lee, Staff Developer Advocate, Databricks
  2. 2. Agenda Building a Unified COVID-19 Data Lake Denny Lee Improving IHME COVID-19 Predictions Scott Black
  3. 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. 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
  5. 5. Building a COVID-19 Data Lake
  6. 6. Improving IHME COVID-19 Predictions
  7. 7. Feedback Your feedback is important to us. Don’t forget to rate and review the sessions.
  8. 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