Business use cases for a machine learning system
Perhaps the first question we should answer is, Whyto use machine learning at all?
Why doesn't MovieStream simply continue with human-driven decisions? There are many reasons to use machine learning (and certainly some reasons not to), but the most important ones are mentioned here:
- The scale of data involved means that full human involvement quickly becomes infeasible as MovieStream grows
- Model-driven approaches such as machine learning and statistics can often benefit from uncovering patterns that cannot be seen by humans (due to the size and complexity of the datasets)
- Model-driven approaches can avoid human and emotional biases (as long as the correct processes are carefully applied)
However, there is no reason why both model-driven and human-driven processes and decision making cannot coexist. For example, many machine learning systems rely on receiving labeled data in order to train models. Often, labeling such data is costly, time consuming...
