Why do we need use cases

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 ML algorithms require a clear purpose to effectively addre problems m. Defining a use case ensures that the ML application is relevent and provides value to a specific task or challenge.

 ML models are only as good as the data they're trained on. A well-defined use case plays a crucial role in ensuring that the right type of data is collected, which is the foundation for training the models to perform the intended tasks accurately it.

 Different ML algorithms are suited to different problems. A specific use case helps select the most appropriate algorithm based on the problem's characteristics, such as regression, classification, or clustering 

A use case defines the criteria for success and how the ML model 's performance will be measured. This is essential for evaluating the ML solution's effectiveness.

 Knowing the use case helps allocate the right resources, including computational power and human expertise, to ensure the ML solution is developed efficiently and effectively 

ML is primarily used to predict future events based on historical data. A specific use      case clarifies the prediction goals and the context in which the model      will operate