It is crucial to identify the right neural network type to solve a business problem efficiently. A standard neural network can be a best fit for most use cases and can produce approximate results. However, in some scenarios, the core neural network architecture needs to be changed in order to accommodate the features (input) and to produce the desired results. In the following recipe, we will walk through key steps to decide the best network architecture for a deep learning problem with the help of known use cases.