If you want to use a library to find the shortest path in a graph, then the input is simply the list of nodes and edges and is easy to understand. You can use a

If you want to use a library to find the shortest path in a graph, then the input is simply the list of nodes and edges and is easy to understand. You can use a third party library to solve the problem without knowing how the algorithm works under the hood. But the arguments to a ML algorithm provided by third-party libraries include various parameters to tune the algorithm and make tradeoffs between accuracy/time etc. Debugging the algorithm for your particular dataset also requires some knowledge of how the algorithm works. But there are use cases where you need not know what's happening behind the scenes. For example, you can use a ML as a Service provider to classify your photos without knowing how their algorithms work.