Machine Learning, Summary, Data Science.
the accuracy of the model and how to validate it, deciding when to retrain a model, and so-called “adversarial settings”, or protecting the models from malicious tampering. Overall, the most common bottleneck in all of these parts is the amount of human interaction and monitoring involved, which