In the machine learning development process, which phase is focused on defining your use case?

Defining your use case is a crucial initial step in the machine learning development process, encapsulated in the phase known as framing the problem. This phase involves clearly articulating the business or research problem you are aiming to solve, as well as determining the objective of the machine learning model. It sets the foundation for the subsequent phases of the development process, including data gathering, feature selection, model selection, and evaluation.

During the framing the problem phase, it is essential to consider the specific requirements and constraints of your project, the stakeholders involved, and the context in which the model will be used. By establishing a well-defined use case, you can better guide your decisions regarding the type of data to collect, the features to engineer, and the appropriate algorithms to utilize. This careful groundwork ultimately influences the success and effectiveness of the machine learning solution.