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Solving the mystery of testing ML-based recommender systems |
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Let's play a quiz. Think of any popular software application where machine learning (ML) is not used! Nothing came into your mind, right? In today's era, ML is indeed the epicenter of software. Most apps have various ML-based segments & one such segment is "recommendations". Tremendous efforts are put in developing such systems. But ever wondered how these systems are tested? Quality assurance takes a backseat here. People perceive that "It's ML, it cannot be tested". But is it really the case? In this presentation, Shibani Gaba will share her journey of exploring and testing recommendation systems. She will bring to the table some of the challenges she faced and share her learnings in order to create impact in these projects. Shibani Gaba Shibani Gaba works as a Lead QA Engineer in New Work SE (Germany). Since 2013, her long experience with testing and wide interests have enabled her to get into all layers of software from UI, API and backend, functional, non-functional, to mobile and ML testing. In addition, Shibani is a certified scrum master, having worked with multiple international teams, bringing forward the Agile Methodology and promoting'quality as a team effort'. This is something that she also advocates as speaker. Shibani has participated in various international conferences such as Testbash, Quest For Quality, EclipeConf and many more.
In this presentation you will learn about recommendation systems based in Machine Learning. |
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