Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications

2. Project Workflow

2.1 Introduction

This chapter focuses on the workflow of executing data science tasks as one-offs versus tasks that will eventually make up components in production systems. We’ll present a few diagrams of common workflows and propose combining two as a general approach. At the end of this chapter you should understand where they fit in an organization that uses data-driven analyses to fuel innovation. We’ll start by giving a little more context about team structure. Then, we’ll break down the workflow into several steps: planning, design/preprocessing, analysis, and action. These steps often blend together and are usually not formalized. At the end, you’ll have gone from the concept of a product, like a recommender system ...