Choosing a Task for Machine Learning
Explore the process of choosing the right machine learning task by identifying the problem, evaluating data availability and task complexity, selecting task types like classification or regression, and setting appropriate evaluation metrics. Learn to iterate and improve models based on performance to build effective ML solutions aligned with your goals.
Choosing a task for ML depends on several factors, including the problem domain, available data, and resources. Here are some general guidelines for choosing a task for ML:
Identifying the problem: First, we need to identify the problem we want to solve. This could be a business problem, a research question, or a challenge in our field.
Determining the data availability: We must determine if we have the necessary data to train an ML model. The amount and quality of ...