AREA COVERED
- Introduction to machine learning
- How does an ML model work?
- Applications of ML in pre-clinical research
- Deep dive into ML use cases
- Key takeaways and learnings
- Avoiding data-specific pitfalls
LEARNING OBJECTIVES
- Understand how a machine learning model works
- Understand ongoing research in the field of pre-clinical research and machine learning
- Discuss use cases where machine learning algorithms will help
- Advantages of machine learning in pre-clinical research
- Companies working on fast-tracking pre-clinical research
- Key takeaways
WHO WILL BENEFIT?
- Machine learning enthusiasts
- Business Analysts
- Business consultants
- Life science leaders
- Regulatory compliance experts
- Introduction to machine learning
- How does an ML model work?
- Applications of ML in pre-clinical research
- Deep dive into ML use cases
- Key takeaways and learnings
- Avoiding data-specific pitfalls
- Understand how a machine learning model works
- Understand ongoing research in the field of pre-clinical research and machine learning
- Discuss use cases where machine learning algorithms will help
- Advantages of machine learning in pre-clinical research
- Companies working on fast-tracking pre-clinical research
- Key takeaways
- Machine learning enthusiasts
- Business Analysts
- Business consultants
- Life science leaders
- Regulatory compliance experts
Speaker Profile
Over 17 years of experience in life sciencesPrevious experience working with Pwc,KPMG and Deloitte,Oracle,MetricStream,Infosys Consulting, HTC and Siemens ResearchActive member of ISACAProfessional associations with ISPE,OCEG,GARP,Carnegie Mellon Swartz Center for entrepreneurshipMaster in Software Engineering, Carnegie Mellon University, Pittsburgh,USBachelors in Computer Science, University of Madras,India
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