Introducing the machine learning workflow
If you’re a data scientist preparing for a technical interview, understanding the machine learning workflow is non-negotiable. Machine learning is concerned with the design and application of algorithms and techniques that allow computers to learn patterns that are often applied to solve business problems.
At its core, the workflow consists of several key stages, beginning with a well-defined problem statement and culminating in the application of a model trained on unseen data. Each stage, whether it’s selecting the appropriate model, tuning hyperparameters, or making predictions, serves as an essential step in the data science process. Mastery of these stages not only sharpens your technical acumen but also equips you with the systematic thinking required to tackle a wide range of data-related problems:
Figure 10.1: Workflow for machine learning projects
The importance of the machine learning...
