Koneoppimistyönkulku
Koneoppimistyönkulku refers to the systematic process of developing and deploying machine learning models. It encompasses all the stages from defining the problem to maintaining the model in production. The typical workflow begins with understanding the business problem and translating it into a machine learning task. This is followed by data collection and preparation, which involves gathering relevant data, cleaning it to remove errors and inconsistencies, and transforming it into a suitable format for modeling. Feature engineering is a crucial step where new features are created from existing ones to improve model performance.
The next stage is model selection, where appropriate algorithms are chosen based on the problem type and