Data Science Project Phases
In our first phase of an ML project, we outline strategic goals. We match the problem with the solution, define the scope of work and plan the development.
Dataset Preparation & Processing
The second stage of project implementation is complex and involves data collection, selection, pre-processing, and transformation. Each of these phases can be split into several steps.
A dataset used for machine learning should be partitioned into three subsets — training, test, and validation sets.
Model exploration, refinement, evaluation, deployment then maintenance.