Why do we need different types of models?

So far, we have invested a significant amount of effort in data processing while focusing on tasks such as noise reduction and annotation. However, we have yet to delve into the models that are employed to work with this processed data. While we briefly mentioned different types of models based on data annotation, including supervised, unsupervised, and reinforced learning, we have not thoroughly explored the user’s perspective when it comes to utilizing these models.

It is important to consider the perspective of the user when employing machine learning models for working with data. The user’s needs, preferences, and specific requirements play a crucial role in selecting and utilizing the appropriate models.

From the user’s standpoint, it becomes essential to assess factors such as model interpretability, ease of integration, computational efficiency, and scalability. Depending on the application and use case, the...