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Testing a Data Science Model
July 14 @ 10:00 am - 11:00 am MDTFree
Laveena shares how she was able to explore the world of data science as a tester when testing a model and how you can apply that if you find yourself in a similar situation. As part of an emerging team, how she was able to contribute value in a new field that she had never tested before.
Having heard from other senior testers that they know of data science teams but no testers testing the models, how do we have enough confidence what is produced is good enough? A model is a statistical black box, how do we test it so we understand its behaviors to test it properly? The main focus should be to help inspire testers to explore data science models.
Join Laveena as she goes through a journey of discovering data science model testing and finding the following takeaways useful, not just for testing a data science model, but for day-to-day testing too.
- Some background of what a data science model is, and how data plays a role in these models. Understand from vast amounts of data, including:
- structured data
- unstructured data
- semi-structured data
- Have a better understanding of what data science is.
- Know how we can test models.
- Know what existing skills we already have that we can apply in a data science team.
- Leave with resources to help our teams’ better structure itself to have confidence in the data produced.
- We’ll look at what did or didn’t work.
Laveena Ramchandani – Senior Consultant – Testing, Miss
Laveena is an experienced Testing Consultant with a comprehensive understanding of tools available for software testing and analysis. She is an energetic, technical-minded professional seeking a position as a Product Experience Analyst. Her aim is to provide valuable insights that have high technical aptitude, and unyielding commitment to work. Being able to inspire more individuals out there in the world be a great achievement.
Joining from London, United Kingdom
LinkedIn: Laveena Ramchandani