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 ...

Get Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.