How does banner regeneration increase conversions?
Machine Learning / AI
What methods are used for selecting negative examples?
What is targeting?
What is a probabilistic conversion model?
How does feature mixing affect the quality of the model?
How to test the identification system in real traffic?
How does early stopping work in trees?
Should the hash content of the identifier be analyzed or should the hash be removed?
How to make the identification process invariant to browser characteristic changes?
What are SSP and DSP?
What methods for combating overfitting exist and how do they work?
What is the algorithm called that uses logarithm loss?
What features influence and can change for a single user, and which do not?
How to cache the most frequent queries in RAG?
What are the features of training on large satellite tiles (memory, IO)?
What data sources for ML have you integrated (DWH, Kafka, S3)?
How does dropout work in neural networks?