Inspiration from some of the world's biggest tech orgs
Picking the right tool for building personalization
Shailvi Wakhlu explains why machine learning and AI products require experimentation to quantify success.
Azadeh Moghtaderi explains why only A/B testing can gauge the magnitude and impact of AI/ML models.
As the cost of implementing ideas goes to zero, evaluating ideas becomes the bottleneck
There is a gold standard for evaluating AI models: Comparing models in AB experiments against business metrics.
Machine learning models cannot be evaluated without AB experiments. The same is true for machine learning teams.
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