Choosing the right models and tuning the parameters for the model are at the core of AI application development. In most cases, there are several algorithms that are applicable to the task, and it may not be clear from the beginning which algorithm will perform best. For example, some algorithms might perform better for small datasets, while others excel on big data. Usually, there are also other constraints to think about, such as runtime or the amount of computational resources available. The best model is the one that achieves a sufficient level of accuracy with the minimum amount of computational resources.
The first step when solving an ML problem is to identify which family of algorithms should be ...
