Ideas from books, articles & podcasts.
The development of AI is creating new opportunities to improve the lives of people around the world, from business to healthcare to education.
It is also raising new questions about the best way to build fairness, interpretability, privacy, and security into these systems.
The way actual users experience your system is essential to assessing the true impact of its predictions, recommendations, and decisions.
The use of several metrics rather than a single one will help you to understand the tradeoffs between different kinds of errors and experiences.
Consider metrics including feedback from user surveys, quantities that track overall system performance and short- and long-term product health (e...
ML models will reflect the data they are trained on, so analyze your raw data carefully to ensure you understand it.
The difference between performance during training and performance during serving—is a persistent challenge.
During training, try to identify potential skews and work to address them, including by adjusting your training data or objective function. During the evaluation, continue to try t...
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