Book Image

Agile Machine Learning with DataRobot

By : Bipin Chadha, Sylvester Juwe
Book Image

Agile Machine Learning with DataRobot

By: Bipin Chadha, Sylvester Juwe

Overview of this book

DataRobot enables data science teams to become more efficient and productive. This book helps you to address machine learning (ML) challenges with DataRobot's enterprise platform, enabling you to extract business value from data and rapidly create commercial impact for your organization. You'll begin by learning how to use DataRobot's features to perform data prep and cleansing tasks automatically. The book then covers best practices for building and deploying ML models, along with challenges faced while scaling them to handle complex business problems. Moving on, you'll perform exploratory data analysis (EDA) tasks to prepare your data to build ML models and ways to interpret results. You'll also discover how to analyze the model's predictions and turn them into actionable insights for business users. Next, you'll create model documentation for internal as well as compliance purposes and learn how the model gets deployed as an API. In addition, you'll find out how to operationalize and monitor the model's performance. Finally, you'll work with examples on time series forecasting, NLP, image processing, MLOps, and more using advanced DataRobot capabilities. By the end of this book, you'll have learned to use DataRobot's AutoML and MLOps features to scale ML model building by avoiding repetitive tasks and common errors.
Table of Contents (19 chapters)
1
Section 1: Foundations
5
Section 2: Full ML Life Cycle with DataRobot: Concept to Value
11
Section 3: Advanced Topics

Chapter 3: Understanding and Defining Business Problems

This chapter covers topics that are the most critical for success and yet are not discussed in detail in data science programs or books. Although the topic of understanding and defining business problems is mentioned very briefly as something that should be done, it is very rare that the discussion will go into how to actually do it properly. In this chapter, we will go into specific tools and methods that can be used to gain an understanding of the system under consideration and determine the problem that needs to be solved.

This section is independent of DataRobot, as DataRobot cannot help you with this part of the process. This is something that a data analyst, a business analyst, or a data scientist has to do. Correctly defining a business problem is hard to do—it is not automatable, and it is also not done properly most of the time. If you gain this skill, you will become invaluable. This is a key area where there...