Perhaps the first question we should answer is, Why to 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...
